OpenAI

ABOUT THE TEAM: OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. ABOUT THE ROLE: We are seeking an experienced Optical Network Engineer to lead Laser related work within our optical interconnect efforts for large-scale compute systems. The role also requires broad, hands-on optical validation experience across IM/DD-based interconnects, working from lab characterization through production readiness and scaled deployment. IN THIS ROLE YOU WILL: - Drive laser-focused requirements and technical direction within the broader optical interconnect roadmap. - Lead evaluation and validation of optical components and subsystems, including laser-based elements, in lab and production-representative environments. - Support end-to-end optical testing for IM/DD interconnects (e.g., module/system bring-up, characterization, debug, and readiness for scale). - Work with external partners to align on development milestones, performance targets, and quality expectations. - Own technical issue triage and resolution across performance, reliability, and manufacturability topics. - Collaborate across internal teams to support integration, rollout, and operational success at scale. YOU MIGHT THRIVE IN THIS ROLE IF YOU HAVE: - Strong experience in laser-focused optical engineering (development, validation, manufacturing readiness, or field support). - Broad hands-on background with IM/DD optical technologies and optical test/debug workflows. - Experience working with external suppliers/manufacturing partners and production-oriented execution. - Demonstrated ability to debug complex technical issues using data-driven methods. - Clear written and verbal communication; ability to influence cross-functional stakeholders. - Advanced degree in a relevant engineering field preferred (or equivalent industry experience). To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional o

ABOUT THE TEAM The Support team is central to ensuring that our customers' experience with our products is nothing short of exceptional. We resolve complex issues, provide technical guidance, and support customers in maximizing value and adoption from deploying our products. We work closely with Sales, Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. OpenAI's customers represent a range of diverse backgrounds and maturity, from early-stage startups to established global enterprises. ABOUT THE ROLE As a Product Engagement Specialist on the User Operations team you will be a hands-on systems builder responsible for making product launches and frontline feedback more scaleable, measurable and actionable across both internal User Operations and external third-party teams.. You’ll be responsible for not only managing the project timelines, but also designing and shipping the workflows, tooling and data systems that connect the voice of the user into actionable improvements for Product and Engineering teams. We’re looking for people who thrive at the intersection of project management, team enablement, and customer advocacy, and enjoy working cross-functionally in a fast-paced, evolving environment. We are also looking for individuals that will not just do the day to day work - but will also be deeply involved in architecting the systems of feedback sharing and collection with our stakeholder groups across Support, Product, and Engineering. Think data systems, not better slide decks. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Design, build, and own scalable systems for launch readiness, feedback capture, triage, synthesis, and routing. - Coordinate product launches across internal User Operations teams and external third party teams to ensure seamless execution and support readiness. - Develop and implement scalable feedback loops between support teams and product/engineering teams, ensuring customer insights are integrated into product development and strategy. - Serve as the voice of the user, advocating for their needs and pain points in product and engineering discussions. - Collaborate with cross-functional teams (e.g., Product, Engineering, Marketing, and Operations) to align on product launch goals and timelines. - Lead efforts to document and standardize launch procedures, ensuring they are easily repeatable and scalable as the product line grows. - Monitor post-launch performance, gathering data from support teams to evaluate product impact and inform future improvements. - Identify potential risks and challenges during product rollouts, proposing solutions to mitigate disruptions to customer service. - Regularly report on the performance of the feedback loop, including key insights, trends, and actionable recommendations for the product roadmap. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have experience in product launch coordination, especially within a customer support environment (internal and/or external). - Bring product management, technical program management, or similarly hands-on experience taking ambiguous problems from discovery through delivery and adoption. - Enjoy working cross-functionally and are skilled at building relationships with Product, Engineering, and Operations teams. - Are technically fluent in areas such as APIs, integrations, data flows, analytics, automation, or lightweight scripting, even if you are not a software engineer. - Are passionate about customer advocacy and have experience translating customer feedback into strategic product insights. - Are highly organized and able to manage multiple projects with competing deadlines. - Have excellent communication skills, with the ability to clearly articulate technical concepts and customer pain points to diverse audiences. - Are proactive and take

About the Team The Physical Security Engineering team designs, deploys, and sustains the systems that protect OpenAI’s people, facilities, and critical infrastructure. We work across global office campuses, warehouses, labs and data centers, partnering with IT, Facilities, Construction, and Security Operations to ensure all environments meet stringent safety, reliability, and compliance requirements. Our team owns security architecture from early site due-diligence through construction, commissioning, and long-term lifecycle management. Role and Responsibilities OpenAI’s corporate footprint is expanding quickly across APAC, and our physical security technology needs to scale with the same level of reliability, consistency, and care. The Corporate Security Technology Group owns the access control, video surveillance, and supporting infrastructure that help protect OpenAI’s people, offices, and events. This role will be the regional technical owner for designing, operating, troubleshooting, and improving those systems across APAC. This person will partner closely with CorpSec, Workplace/REW, IT/NetEng, and security integrators to bring new offices online, maintain system health, resolve regional escalations, and improve how our physical security systems are documented, supported, and used. We’re looking for someone with deep subject matter expertise in Windows OS/Servers, networking and switching, and systems integration support, with the ability to diagnose issues across the full stack from endpoint devices and network infrastructure through servers, databases, and enterprise security platforms. What you’ll do - Own day-to-day technical support and administration for physical security systems across APAC, including access control, video management, and related infrastructure. - Support new office buildouts by reviewing designs, coordinating vendors, validating system readiness, and ensuring clean operational turnover. - Troubleshoot complex issues across Genetec, Windows OS/Servers, databases, networking, switching, integrations, and field hardware. - Partner with IT/NetEng on connectivity, identity, infrastructure, firewall, VLAN, switch configuration, IP schema, routing, and device connectivity dependencies. - Support integrations between physical security systems and adjacent enterprise systems, including identity, access management, monitoring, and operational workflows. - Create and maintain drawings, site documentation, operating procedures, and training materials for administrators and end users. - Help reduce operational toil by improving standards, documentation, monitoring, vendor handoffs, and repeatable support practices. What’s success? APAC sites open and operate with reliable, well-documented physical security systems. Regional partners know who owns technical decisions, urgent issues are diagnosed quickly, and vendors are held to a clear quality bar. The hire raises the operating standard for APAC while helping the global team create more repeatable deployment, support, integration, and troubleshooting practices. Non-negotiable outcomes - No avoidable access control, video coverage, or system reliability gaps caused by unclear ownership, weak vendor follow-through, or poor technical turnover. - Faster and cleaner resolution of regional incidents, odd-hour escalations, and new office launch issues. - Strong technical ownership across Windows OS/Servers, networking, switching, physical security platforms, and integration dependencies. - Strong partnership with CorpSec Operations/Protection, Workplace/REW, IT/NetEng, and regional vendors. - Better documentation, training, and handoff processes for admins, end users, and cross-functional partners. - A scalable regional support model that can keep pace with OpenAI’s APAC growth. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabil

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design and build systems to manage both cloud and bare-metal fleets at scale. - Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. - Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. - Automate infrastructure processes, reducing repetitive toil and improving system reliability. - Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. - Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: - Have strong software engineering skills with experience in large-scale infrastructure environments. - Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). - Have deep expertise in server-level systems (e.g., systems, containerization, Chef, Linux kernels, firmware management, host routing). - Are passionate about optimizing the performance and reliability of large compute fleets. - Thrive in dynamic environments and are eager to solve complex infrastructure challenges. - Value automation, efficiency, and continuous improvement in everything you build. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return

About the Team We’re hiring software engineers to make the Workload team more productive. The Workload team maintains the core components of OpenAI’s training and inference frameworks and helps execute frontier experiments. About the Role We’re looking for someone who cares about the developer experience of working in and around OpenAI’s core training and inference frameworks. In this role you will: - Be responsible for optimizing the development workflows of the engineers around you - Work within various Workload teams to address their specific needs, but collaborate with the centralized teams that own various aspects of development experience - Optimize iteration speed, both broadly, and in particular by optimizing specific teams’ CI - Improve reliability, for instance, by driving testing strategy for particular components - Work through the long tail of things that it takes to build libraries and systems that will delight researchers You might thrive in this role if: - You are motivated by helping people. You believe a thing that separates great teams from good teams are the players willing to do whatever work it takes, without ego. - You believe in the power of developer experience. Something magical happens when people can quickly and confidently iterate on a simple codebase, but this magic is fragile and must be fought for. - When you see someone trip over something, no matter how small, your first instinct is asking yourself what it would take for that to not happen again. Your second instinct is clicking merge on the PR you’ve already written to make it so. - You are pragmatic. You have the ability to see the world through a perfectionist’s eyes, but are not yourself a perfectionist. You know which problems to pick and when to switch to making progress on a different problem. - You like going end-to-end on things. You love co-design — that feeling when you were only able to find the right solution because you both deeply understand the users that interact with a system and the system itself. - You like working with Python About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions optimized for advanced AI workloads. We collaborate across research, software, and external hardware partners to design and deploy next-generation AI systems at scale. Our team works closely with silicon vendors and system partners to evaluate emerging technologies, validate performance characteristics, and ensure that hardware capabilities translate effectively to real-world AI workloads. About the Role We are seeking a 3P Hardware Architecture Expert with deep expertise in GPU and accelerator architectures to engage directly with silicon vendors and guide hardware decisions for AI infrastructure. In this role, you will evaluate architectural tradeoffs across compute, memory, and interconnect systems, translating vendor specifications into real-world workload impact. You will play a critical role in early silicon evaluation, benchmarking, and performance validation, helping ensure that next-generation hardware meets the needs of our workloads. This role is highly hands-on and requires both deep technical understanding and the ability to engage at a high level with partners such as NVIDIA and AMD on architectural direction and design tradeoffs. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities - Engage deeply with silicon vendors (e.g NVIDIA & AMD) on GPU and accelerator architecture tradeoffs. - Analyze and interpret performance, power, and efficiency characteristics of next-generation hardware. - Translate vendor specifications into expected real-world performance for AI workloads. - Evaluate architectural aspects including: - compute throughput and utilization - memory systems (HBM, cache hierarchies, bandwidth constraints) - data types and precision tradeoffs (FP16, BF16, FP8, etc.) - interconnect and scaling behavior. - Run benchmarks and profiling to validate hardware performance against workload requirements. - Lead early bring-up and evaluation of engineering sample (ES) silicon. - Partner with performance modeling and system architecture teams to align measured vs. modeled behavior. - Provide actionable feedback to vendors to influence future silicon design and roadmap decisions. Qualifications - Have deep expertise in GPU or accelerator architecture, including performance and power tradeoffs. - Understand AI workload behavior and how it interacts with hardware design choices. - Are comfortable engaging directly with silicon vendors at a technical architecture level. - Have hands-on experience with benchmarking, profiling, and performance analysis. - Can translate low-level hardware details into system-level and workload-level impact. - Are equally comfortable in theory (architecture) and practice (measurement/validation). - Thrive in environments where you bridge internal teams and external partners. Preferred Skills - Experience working with or at companies like (e.g NVIDIA & AMD) or similar silicon providers. - Familiarity with AI accelerator stacks, including GPUs, custom ASICs, or emerging architectures. - Experience with early silicon bring-up or hardware validation workflows. - Strong understanding of memory systems (HBM, DDR, cache hierarchies) and data movement bottlenecks. - Experience with performance tooling, microbenchmarks, and workload characterization. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and

Overview: The Data Acquisition team within the Foundations organization at OpenAI is responsible for all aspects of data collection to support our model training operations. Our team manages web crawling and GPTBot services and works closely with Data Processing, Architecture, and Scaling teams. We are looking for a skilled Full-Stack Engineer to join our Data Acquisition team to build and optimize the interfaces and tools that power our data infrastructure. RESPONSIBILITIES: - Develop and maintain full-stack applications that support data acquisition, including internal tools and dashboards. - Collaborate closely with cross-functional teams, including Data Processing, Architecture, and Scaling, to ensure seamless data ingestion and workflow management. - Design and implement APIs to facilitate data interactions between internal services and external data sources. - Enhance user experience by developing intuitive web-based interfaces for managing and monitoring data pipelines. - Optimize backend services for performance, scalability, and security in a distributed computing environment. - Work with legal and compliance teams to ensure our data acquisition processes adhere to privacy regulations and best practices. - Deploy and maintain infrastructure using Kubernetes and Infrastructure-as-Code (IaC) methodologies. - Analyze system performance, conduct experiments, and improve data workflows to maximize efficiency. QUALIFICATIONS: - BS/MS/PhD in Computer Science or a related field. - 4+ years of industry experience in full-stack development. - Proficiency in frontend frameworks (React, Vue, or similar) and backend technologies such as Python, Node.js, or Go. - Strong expertise in RESTful APIs, GraphQL, and database design (SQL and NoSQL). - Experience building data-intensive applications that handle large-scale datasets. - Familiarity with cloud platforms (AWS, GCP, or Azure) and container orchestration (Kubernetes, Docker). - Prior experience with web crawling and large-scale data processing is a plus. - Strong problem-solving skills and ability to balance multiple tasks in a fast-moving environment. - Excellent communication and collaboration skills. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and mainta

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Threat Intelligence team protects OpenAI’s technology, people, research, and infrastructure by proactively identifying and disrupting adversaries who seek to compromise our systems or misuse our models. We investigate sophisticated threats, build tooling to scale and augment analysis, and deliver intelligence that shapes security strategy and equips leadership with timely, risk-aware insights. We combine technical depth, investigative rigor, and strong cross-functional partnerships to uncover threats and drive impact across OpenAI’s security and research organizations. About the Role As a Technical Threat Investigator at OpenAI, you will help protect the company from sophisticated adversaries targeting OpenAI and the broader ecosystem, as well as those attempting to misuse our models in support of cyber operations. This is a deeply investigative role. You will independently conduct complex, end-to-end investigations into capable threat actors to understand their behavior, infrastructure, emerging techniques, and how AI is integrated into their workflows. You’ll use these insights to proactively identify malicious activity and drive detection, disruption, enforcement, and safety improvements across the company. You’ll translate your investigative findings into durable solutions that scale impact. You’ll build and own lightweight tooling, automate where it matters, and create AI-assisted workflows to make investigations faster, more repeatable, and more effective over time. In this role, you will: - Conduct deep, end-to-end investigations into sophisticated threat actors interacting with OpenAI’s models, products, and broader ecosystem. - Think like an adversary — model attacker behavior, anticipate misuse patterns, and proactively hunt for, identify, and disrupt malicious activity. - Leverage internal telemetry, OSINT, vendor data, and in-house safety systems to produce high-confidence findings on adversarial use of our models in cyber operations, platform abuse, and threats targeting OpenAI. - Translate investigative findings into concrete improvements across detection, enforcement, intel, and safety pipelines. - Build tooling, scripts, automations, and agentic workflows that scale investigative throughput and reduce manual effort. - Prototype solutions in ambiguous and emerging problem spaces, including new product surfaces, novel attacker behaviors, and areas where existing coverage may be limited. - Partner closely with teams across Security, Safety Systems, Product Policy, and Integrity to operationalize findings and drive meaningful outcomes. - Produce clear, high-signal written outputs and recommendations that inform decision-making across technical and executive stakeholders. You might thrive in this role if you have: - Experience in threat intelligence, incident response, offensive security, or a closely related field. - Solid experience investigating sophisticated threat actors, including model misuse, platform abuse, or other adversarial activity in complex environments. - A strong understanding of adversary behavior, infrastructure, and tradecraft, and the ability to apply that understanding to proactive investigations. - Demonstrated ability to independently drive deep technical investigations from ambiguous signals through to clear, actionable findings. - Experience using AI to extend or accelerate investigative workflows. - Strong scripting ability and comfort building lightweight automation, investigative tooling, or workflows that improve scale and repeatability. - Strong ability to leverage telemetry from diverse systems and vendors to drive investigations, including directly querying, extracting, and stitching together data where needed. - Strong written and verbal communication skills, especially the ability to translate technical investigations into high-signal output

About the Team OpenAI’s mission is to ensure that general-purpose artificial intelligence benefits all of humanity. Our Communications team’s ethos is to support OpenAI’s mission and goals by clearly and authentically explaining our technology, values, and approach to safely building powerful AI. About the Role OpenAI is seeking an experienced communications professional to join our Platform & Research Communications team. This role will work closely with the Research Communications Lead and partner deeply with safety researchers, alignment researchers, and cross-functional teams to shape how OpenAI’s safety research is understood by researchers, journalists, policymakers, and the broader public. This position is responsible for developing and executing external communications strategies around OpenAI’s safety research—from alignment and evaluations to broader work that helps advance the safe development and deployment of increasingly capable AI systems. The ideal candidate brings strong science or technical fluency, excellent storytelling instincts, and experience helping researchers communicate complex work with clarity, accuracy, and nuance. You will partner closely with research leadership, individual researchers, policy, product, safety, legal, and cross-functional communications teams. This role requires both strategic judgment and hands-on execution in a fast-moving environment where research, public understanding, and high-stakes safety narratives intersect. This role is based in San Francisco, CA and follows a hybrid schedule (three days per week in office). Relocation assistance is available. In this role, you will: Shape Safety Research Narratives Develop clear, credible external narratives around OpenAI’s safety research, including alignment, evaluations, preparedness, interpretability, and other areas connected to the safe development of frontier AI. Translate complex technical work into accessible stories without oversimplifying, overstating impact, or creating unnecessary alarm. Help define and reinforce OpenAI’s POV on key safety research topics and how they connect to OpenAI’s broader research roadmap and mission. Partner Deeply with Researchers Work directly with safety and alignment researchers to understand their work, identify the most important ideas, and help position those ideas publicly. Serve as a communications thought partner to researchers—helping them anticipate questions, clarify implications, and communicate with precision. Build communications plans that help researchers share their work through the right channels, at the right level of depth, and with the right context. Lead Proactive Storytelling & Content Strategy Develop proactive storytelling opportunities across blogs, explainers, video, podcasts, events, and other channels beyond traditional media. Help identify creative ways to elevate safety research and make the work more legible to expert and non-expert audiences. Look across the safety research portfolio to identify broader themes, narrative opportunities, and moments where OpenAI can contribute meaningfully to public understanding. Support Research Launches & Publications Partner with research teams to plan communications for major papers, evaluations, model-related research, safety initiatives, and other technical publications. Collaborate with editorial, design, social, policy, and research teams on blogs, explainers, visuals, briefing materials, and supporting content. Ensure launches are grounded in evidence, appropriately scoped, and aligned with OpenAI’s safety, policy, and communications priorities. Lead Research-Focused Media Engagement. Build and maintain trusted relationships with science, technology, AI, and business journalists who cover frontier AI and safety research. Manage proactive and reactive media engagement related to safety research announcements, papers, collaborations, and emerging narratives. Prepare researchers and executives for interviews, briefings, eve

About the Team The Agent Infrastructure team at OpenAI is responsible for building systems that enable training and deployment of highly useful AI agents, both internally and for the world. We work hand-in-hand with researchers to design and scale the environment in which agentic models are trained – providing a workspace for AI models to execute code, debug issues, and develop software just as human SWEs do. Our training environment for agentic models operates at an extremely high scale and has the flexibility to emulate any environment in which an agent might work. At the same time, our team builds and maintains OpenAI’s core platform for the deployment and execution of agents in production. Our systems power products such as Codex, Operator, tool use in ChatGPT, and future agentic products. Some of the most challenging technical problems in scaling the capabilities and utility of agents and agentic models lie in the infrastructure layer – and our team is focused on building the research and production systems that enable OpenAI to train the most capable models in the world, and maximize the utility of our agentic products for users around the world. About the Role As a Software Engineer on the Agent Infrastructure team, you will have the opportunity to work closely with both research and product at OpenAI - building and scaling systems to train highly capable agentic models, and building the platform and integrations to launch new agents to hundreds of millions of users worldwide. Your work will consist of both building new capabilities - standing up the infrastructure and integrations needed to train more complex agentic models - and rapidly scaling these new capabilities to some of the largest compute clusters in the world. At the same time, you’ll be instrumental to the launch of agentic products at OpenAI - building, maintaining, and scaling the production platform on which all agents run. We’re looking for people with deep experience building AI infrastructure and who are used to working closely with researchers to build high-performance systems at massive scale for novel use cases. This role is based in San Francisco, CA or New York City, NY. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Push massive compute clusters to their limits. You will be a core contributor to a novel container orchestration platform built in-house by our team to scale far beyond what’s possible with systems like Kubernetes. - Develop and maintain FastAPI and gRPC APIs that serve as the interface for our agentic infrastructure used both in training and production. - Use Terraform to stand up and evolve complex infrastructure for both research and production. - Collaborate with research teams to stand up and optimize systems for novel AI training runs and experimental applications. You might thrive in this role if you: - Have deep experience working on large-scale machine learning infrastructure. You know how to reason about training at scale, identifying bottlenecks and engineering solutions to optimize system performance in training environments. - Know how to build new things from 0-1 quickly, and then scale them 1,000,000x. - Have a keen eye for performance and optimization. You know how to squeeze the most performance out of complex, globally-distributed systems. - Know your way around cloud platforms and work with infrastructure-as-code tech like Terraform. - Are driven by solving complex, ambiguous problems at the intersection of infrastructure scalability, virtualization efficiency, and agentic capabilities. - Have deep technical expertise in virtualization and containerization technologies (e.g. Kata, Firecracker, gVisor, Sysbox) and are passionate about optimizing runtime performance. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the

About the Team OpenAI's Research Data Team exists to accelerate the evaluation, safety and capabilities of our models and products. Made up of technical operators and software engineers, we design the methods in which we acquire and create data. About the Role As a Technical Program Manager (TPM), Data Acquisition, you will partner with research, engineering, and operations to design and implement pragmatic solutions for acquiring data. You will be a key interface between our research roadmap and external data offerings. This role is based in our San Francisco HQ and will be part of a team of TPMs pushing the frontier of data acquisition. In this role, you will: - Partner deeply with research: Work with researchers to scope data needs, define success criteria, and translate priorities into clear execution plans. - Shape the data acquisition pipeline: Identify, evaluate, and advance high impact data opportunities - balancing research value, feasibility, quality, and responsible execution. - Unblock yourself: Move work forward even when the path is unclear — using technical judgement, creative problem solving, and scrappy execution to make progress while longer-term solutions are still forming. - Build lightweight systems and visibility: Use SQL, Python, dashboards, and simple tooling to track performance, quality, and blockers. - Drive technical roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. - Scale your impact: Equip vendors and internal teams with the context, standards, and operating rhythms needed to focus on the most important problems. You’ll thrive in this role if you: - Are proficient in SQL and Python for analysing datasets, querying databases, building dashboards, and generating actionable insights. - Are comfortable using APIs, automation, and AI tools such as Codex to accelerate workflows, remove manual overhead, and upskill quickly in unfamiliar technical areas.Experience sourcing, evaluating, or working with startups, founder and vendors - Are excited to understand the technicalities of cutting-edge AI research and work alongside researchers from instantiation to launch. - Can move fluidly between research context, commercial execution, and data operations. - Want to get your hands dirty; grit and creative problem solving will be required daily - Learn technical concepts exceptionally quickly, seeking out knowledge to become proficient in areas that are new to you - Operate with high horsepower, are adept at frequent context switching and working on multiple projects at once with expansive ownership, and ruthless prioritization - Thrive in dynamic environments and can navigate ambiguity with ease About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Ch

ABOUT THE TEAM OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. ABOUT THE ROLE OpenAI is seeking a System Power Engineer to characterize, measure, and optimize power consumption across our embedded hardware products. In this role, you will work closely with Electrical Engineering and system software teams to build power test automation, measure subsystem-level power usage, and drive improvements that directly impact battery life, thermal behavior, charging performance, and system reliability. You will help establish the methodologies and metrics used to understand and improve power efficiency across real-world product experiences, from controlled lab environments to representative day-in-the-life usage scenarios. This role requires hands-on experience with embedded hardware platforms, power instrumentation, and the analysis of power profiles and system behavior. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. IN THIS ROLE, YOU WILL: - Define and develop power testing automation to evaluate system behavior across a range of workloads and operating conditions. - Measure subsystem-level power consumption using power breakout probes and other lab instrumentation. - Develop and execute power characterization tests spanning basic workloads, complex mixed-use scenarios, and representative day-of-use experiences. - Partner closely with Electrical Engineers to identify opportunities to improve system power efficiency. - Collaborate with software engineering teams to optimize energy usage in scenarios that impact battery life, device temperature, charging performance, and overall user experience. - Define repeatable power benchmarks and measurement methodologies to assess launch readiness and track performance throughout the product lifecycle. YOU MIGHT THRIVE IN THIS ROLE IF YOU HAVE: - Experience measuring and optimizing power consumption on embedded hardware platforms. - Demonstrated experience designing and operating complex hardware-in-the-loop laboratories and orchestrating device testing at scale. - Experience analyzing power profiles and correlating them with overall system performance. - Experience collaborating cross-functionally with Electrical Engineering, embedded software, systems, and product teams. - Experience defining repeatable power benchmarks and launch readiness metrics for hardware products. - Strong proficiency in Python, experience in C/C++ PREFERRED QUALIFICATIONS - Familiarity with statistics, experimentation methodologies, or data science concepts. - Experience performing subsystem-level power measurements using power breakout probes or similar lab instrumentation. - Experience working with battery-powered consumer products and optimizing for battery life, thermals, and charging performance. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability,

ABOUT THE TEAM The Cooperative AI team is scaling to devices and embedded operations and user experiences. Our model-powered scaled workforce and knowledge system are moving on to the edge and powering our devices and edge experiences. By leveraging OpenAI’s state-of-the-art models and technologies, in production and in the lab, we develop systems that reason and work autonomously with customers and with our workforce responsible for operational work. We carry real workloads for critical systems across finance, sales, customer support, integrity, product insights, internal operations, and now devices to drive insights into product and industry. We partner closely with internal teams and external customers globally, operating in a hyper-fast feedback loop where many of our users are just a few steps away. This proximity allows us to iterate quickly, validate impact in real time, and accelerate industry impacting learnings and systems builds. We are a highly multidisciplinary, self-contained team focused on transforming the workplace via smart systems, knowledge, scalable and reliable primitives that apply world-class AI capabilities across domains. Our mission is to learn fast and transform how humans collaborate with AI at scale. ABOUT THE ROLE We are looking for a Technical Lead Manager to lead a team of engineers building AI-native embedded experiences and operations-forward systems. In this role, you will perform both hands-on technical leadership and small team management. You will drive business outcomes, architecture and technical strategy for complex systems, contribute directly to implementation, and help grow a high-performing team. You will work closely with internal stakeholders to understand operational challenges, identify high-leverage opportunities for automation, and deliver solutions that create measurable impact. This role is ideal for someone who enjoys moving between technical design, coding, mentoring engineers, and working directly with users to understand their problems. IN THIS ROLE, YOU WILL: - Lead the technical direction, architecture, and execution of critical Cooperative Systems initiatives. - Manage and mentor a team of engineers while maintaining meaningful hands-on technical involvement. - Partner closely with stakeholders across Support, Operations, Finance, IT, Sales, Legal, and other functions to identify opportunities for AI-driven improvements. - Design and build production systems that leverage large language models and other AI technologies. - Drive engineering excellence through strong technical decision-making, code quality, operational rigor, and thoughtful system design. - Balance rapid experimentation with long-term platform investments. - Establish technical roadmaps and execution plans for projects spanning multiple teams. - Coach engineers through technical challenges, career growth, and project execution. - Help shape the culture, processes, and engineering practices of a growing organization. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have experience leading engineering projects involving consumer devices and/or embedded systems - Enjoy building products and systems in ambiguous, fast-moving environments. - Are comfortable moving between architecture discussions, coding, stakeholder meetings, and team leadership. - Have strong systems design and software engineering fundamentals. - Are excited about applying AI to solve real-world operational problems. - Communicate effectively with both technical and non-technical audiences. - Have a track record of delivering complex, cross-functional initiatives from concept through production. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs

About the Team The Agent Enablement team works across engineering, product, design, and research to bring our technology to the world. We seek to learn from deployment and broadly distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. We aim to make our innovative tools globally accessible, transcending geographic, economic, and platform barriers. Our commitment is to facilitate the use of AI to enhance lives, supported by rigorous insights into how people use our products. About the Role We are looking for experienced full-stack engineers to join our new Agent Enablement team. Our goal is to design and grow an open ecosystem of agent-enabled sites and services. This is a wide-ranging role: you’ll build new user and agent identity protocols, user experiences to control and observe agents across web, desktop, and mobile, and much more. We will rely on you to drive our technical decisions while also steering our product and partnership direction, optimizing for both short-term impact and long-term success of the ecosystem. We value engineers who are impact-driven, autonomous, and adept at removing barriers to forward progress. In this role, you will: - Design the primitives and protocols for an open agent ecosystem, enabling our users’ agents to make the best use of sites and services across the internet. - Build a next-generation user experience to observe and control agents, across web, desktop, and mobile. - Evolve our approach to token consumption across subscriptions and API customers. - Execute on fast-paced projects in collaboration with research, design, data science and other product engineering teams. - Work closely with our strategic customers and partners to grow the ecosystem. You might thrive in this role if you: - Have strong full-stack engineering skills and experience shipping customer-facing products from concept to production. You’re comfortable working across frontend, backend, APIs, data models, and product design. - Are comfortable with ambiguity and rapidly changing conditions. You view change as an opportunity to bring structure and clarity, and you have a track record of turning high-level ideas into successful outcomes. - Have worked closely with users and customers, and can translate feedback into product improvements. - Are familiar with enterprise software concepts such as identity, permissions, governance, compliance, and billing. - Enjoy fast-moving zero-to-one environments and are excited to pursue an internet-wide vision. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse a

About the Role OpenAI’s Applications organization spans several rapidly scaling businesses across Consumer, Enterprise, Developers, and Hardware. As OpenAI expands globally, the international business is becoming an increasingly important driver of growth, requiring deeper financial visibility, regional coordination, and market-specific investment decision-making. We are hiring a senior Strategic Finance thought partner to work closely with the Business Finance Officer (BFO), regional leadership and other Strategic Finance teams to drive the financial performance of OpenAI’s international business. This role operates at the intersection of strategy, finance, and operations. You’ll help leadership understand regional performance drivers, allocate investment effectively across markets, and ensure the organization scales globally with strong financial discipline. You’ll also focus on the highest-leverage international priorities: building financial visibility across regions, improving operating rigor, identifying growth opportunities and risks, and ensuring alignment across regional leaders and central functional teams. This role is based in our San Francisco HQ. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Periodic international travel is expected, with potential opportunities to live and work from one of our regional offices over time. In this role, you will: - Own financial visibility and performance management across OpenAI’s international business, including regional revenue, growth, investment efficiency, and operating metrics. - Partner with regional leaders and functional teams to identify opportunities, risks, and operational bottlenecks across key international markets. - Support international expansion planning by helping evaluate market opportunities, investment priorities, and regional scaling strategies. - Develop executive-level reporting and financial narratives to help leadership understand international business performance and inform strategic decision-making. - Coordinate cross-functional planning and forecasting processes across international regions, ensuring alignment between regional teams, Strategic Finance, Data Science, GTM, and Corporate Finance. - Help establish scalable operating frameworks and governance processes that enable OpenAI to manage a rapidly growing global business with increasing rigor and consistency. - Drive international business reviews and recurring operating cadences, helping leadership track progress against regional goals and quickly surface emerging issues. - Partner across the finance organization to support public-company-readiness initiatives and improve the quality, consistency, and scalability of international reporting. - Help design and implement agentic workflows and AI-enabled operating processes that improve financial visibility, forecasting, and execution across global teams. You might thrive in this role if you have: - 10+ total years of progressive experience in Investment Banking, Management Consulting, Private Equity, and Strategic Finance. - 4+ years of direct experience Strategic Finance at a high-growth technology company, ideally publicly traded. - Exceptional modeling and analytical skills, with the ability to translate complex business drivers into clear, actionable frameworks. - A proven ability to communicate verbal and written insights at the executive level; and to and influence cross-functional stakeholders at all levels. - Deep curiosity about disparate business models and how a wide range of end markets will be shaped by AI. - Strong organizational and process management skills, with a talent for orchestrating multiple parties to achieve an outcome. - An enthusiastic "roll up your sleeves" mentality and an ability to deal effectively with ambiguity to thrive in an unstructured, fast-paced environment‬. - High enthusiasm for experimentation with and the deployment of AI. About OpenAI Open

ABOUT THE TEAM The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software is reliable, testable, and ready to ship. We design and maintain automated test frameworks, hardware-in-the-loop labs, and release pipelines that keep quality signals trustworthy and enable rapid, safe product launches. Our work spans developer tools, automation, systems integration, and cross-team collaboration to ensure every release meets the highest standards. ABOUT THE ROLE As a Software Engineer, Quality and Developer Tools, you will build and own the systems that validate our device software—from test frameworks and regression infrastructure to hardware-in-the-loop labs and release gates. You’ll design the tooling and automation that keep quality signals trustworthy, integrate them into CI/CD, and make it easy for engineers and QA vendor technicians to execute reliable, repeatable workflows. We’re looking for engineers with deep experience in software quality, automation, developer tooling, and hardware-software integration who thrive on building scalable, reliable systems for validation and release readiness. This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Test infrastructure & frameworks: Design, implement, and maintain a unified test framework for device software across unit, integration, system, and end-to-end testing, with reproducible runs and integrations with GitHub, Linear, and Slack. - CI/CD integration & releases: Integrate test suites with Buildkite, enforce promotion criteria for staging and production, auto-file regressions, and publish traceable artifacts and release notes. - Hardware-in-the-loop lab design & orchestration: Plan and bring up racks, power and networking systems, and orchestration for device testing; support automated flashing, provisioning, and telemetry capture. - Automation and developer tooling: Develop tools for API and firmware validation, result triage, log capture, replayable bug reports, and workflows that improve engineering velocity and debugging efficiency. - Quality signals, metrics, and flake control: Build dashboards and alerts for pass rates, stability, and release readiness; detect and quarantine flaky tests; drive root-cause analysis with owners; and track delivery metrics that protect release health. - Vendor enablement: Create clear procedures and tooling that allow QA vendor technicians to execute repeatable processes, review their reports, and maintain a queue of rig maintenance and repairs. - Cross-team collaboration: Partner with embedded and systems software teams on testability, and with release infrastructure engineers on pipelines, signing, staged rollouts, and rollback/forward strategies. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have deep experience building software quality, test automation, or developer tooling systems for hardware products shipped at scale. - Are proficient in Python, C, C++, or Rust, and have strong Linux fundamentals, including processes, networking, storage, and udev/systemd. - Have experience building CI/CD pipelines, artifact management systems, and reproducible or isolated test environments. - Have demonstrated success designing and operating hardware-in-the-loop labs and device orchestration systems at scale. - Are fluent with test reliability techniques such as failure triage, flake detection and quarantine, and signal-quality guardrails. - Have strong debugging skills across software, firmware, devices, and release infrastructure. - Work well across teams and enjoy improving the systems that make engineering and release processes more scalable and reliable. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities o

About the Team Full Stack engineers within the Fleet Scheduling team are dedicated to building intuitive and scalable interfaces that empower researchers to efficiently manage AI workloads across some of the largest supercomputers in the world. Our focus is on developing robust, high-performance systems that provide real-time insights, resource tracking, and seamless interaction with complex infrastructure. We aim to optimize resource allocation, minimize operational overhead, and create user-friendly tools that enhance researcher productivity and system transparency. About the Role You will design, develop, and operate web-based systems that provide a powerful and intuitive interface to OpenAI’s supercomputing clusters. You will collaborate closely with researcher, product and infrastructure teams to deliver scalable solutions that enable seamless monitoring, job scheduling, and resource management. This is an opportunity to work at the cutting edge of AI infrastructure, designing tools that scale to exascale workloads while maintaining usability and performance. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design and develop full-stack web applications to track, monitor, and manage large-scale AI workloads in real time. - Collaborate with researchers and infrastructure teams to translate complex operational needs into intuitive UIs and scalable backends. - Build data visualization tools (e.g., Gantt charts, dashboards) to provide insights into job scheduling and resource allocation. - Optimize backend services to handle massive data throughput while ensuring low-latency performance and high availability. - Implement frontend components that provide seamless interactions with scheduling, storage, and compute systems. - Ensure system security, reliability, and scalability across globally distributed supercomputing infrastructure. You might thrive in this role if you: - Significant experience in full-stack development, with expertise in modern frontend frameworks (React, Vue, or Angular) and backend technologies (Python, Go, or Node.js). - Experienced in building scalable, high-performance web applications for complex distributed systems. - Strong understanding of RESTful and GraphQL APIs, distributed databases, and cloud infrastructure (especially Azure). - Execution-focused with a keen eye for usability, performance, and scalability in enterprise-scale systems. - Comfortable working in fast-paced, highly collaborative environments with tight timelines and evolving priorities. Bonus points if you: - Have experience working with Kubernetes, Docker, and cloud-native application deployment. - Understand AI/ML workload scheduling and orchestration challenges. - Have experience with real-time data processing, visualization libraries, and observability tooling. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified appl

About the Team Safety Systems works to ensure OpenAI’s most capable models can be developed and deployed responsibly. Our work spans evaluations, safeguards, red teaming, deployment decisions, and the systems that help OpenAI understand and reduce risk as models become more capable and widely used. Within Safety Systems, the Trustworthy AI team is growing its safety transparency function: a practice focused on helping external audiences understand OpenAI’s technical safety work with greater clarity, rigor, and continuity. We create and improve the public artifacts that explain how our systems are evaluated for safety, what safeguards we build, what decisions we make, and where uncertainty remains. This work includes system cards, the Deployment Safety Hub, safety-related blogs, public governance documents, and other outputs that communicate technical safety topics to external audiences. It also includes building new ways to make technical safety information easier to understand, navigate, and use—including AI-assisted workflows, data visualizations, and interactive tools that make complex technical work more legible over time. About the Role We are looking for a Safety Transparency Editor to own the editorial quality of key safety transparency artifacts and systems. This is a hands-on role for someone who can write crystal-clear, pitch-perfect explanations of the hardest and highest-stakes technical safety topics that OpenAI tackles, and who can lean into AI to build systems that help the broader organization do this work better. Your core responsibility is to shape and execute how our technical safety work is externally communicated: identifying the narrative thread, exercising judgment about which details matter, determining where additional context, explanation, or supporting evidence is needed, translating complexity without sacrificing precision, and helping external audiences understand both the safety measures we’ve taken and the uncertainties that remain. To do this work effectively, you will need to be comfortable educating yourself, using AI tools and existing internal evidence, about the nuances of technical safety work taking place across OpenAI. You will serve as the editorial driver behind system cards and related transparency materials, partnering closely with Safety Programs, researchers, evaluators, red-teamers, policy experts, legal partners, product marketing and communications teams, and other launch stakeholders. You will transform complex technical safety topics into public-facing artifacts that are rigorous, accessible, and faithful to the underlying substance. You’ll also be expected to use AI deeply in your own practice—not simply as a learning and drafting tool, but as a means of rethinking how this work gets done. You should instinctively look for opportunities to build workflows, automate repetitive tasks, improve consistency, and create systems that enable the organization to produce high-quality transparency artifacts at scale and speed. This role demands deep ownership and accountability. The ideal candidate is equally at home refining a tricky explanation of a nuanced technical point, and investing in building systems that make the next ten explanations easier to produce. This role is ideal for someone who combines the judgment of an exceptional editor with the mindset of a builder. You should be comfortable using your voice and judgment while approaching the work with humility, intellectual honesty, and a deep respect for technical nuance. In This Role, You Will Serve as the narrative DRI for system cards and related transparency artifacts from initiation through publication. Partner with the Safety Programs team, researchers, evaluators, red-teamers, policy experts, legal teams, communications partners, and launch teams to translate technical findings into public-facing materials. Write clear, precise explanations of highly technical safety topics for external audiences without sacrificing rig

About the Role We are seeking a Tokens-as-a-Service (TaaS) Engineer to help build the systems that convert large-scale infrastructure capacity into measurable, reliable token throughput for OpenAI workloads. In this role, you will work across performance benchmarking, tokenomics, model porting, infrastructure integration, systems tooling, and operational monitoring. You will help connect partner and first-party compute environments into OpenAI’s infrastructure stack, ensuring GPU capacity can be onboarded, measured, monitored, and optimized against real workload outcomes. Key Responsibilities - Develop systems and tooling to measure, monitor, and improve token throughput across first-party and partner-owned compute environments. - Support performance benchmarking, tokenomics analysis, and model porting across heterogeneous infrastructure environments. - Build tooling to integrate external or partner infrastructure into OpenAI’s internal compute, observability, and workload management systems. - Develop and monitor operational metrics including billing, usage, SLAs, utilization, reliability, and throughput. - Identify bottlenecks across hardware, networking, software, and workload enablement that prevent capacity from becoming productive tokens. - Partner with compute, infrastructure, networking, finance, and operations teams to translate raw capacity into usable workload-serving capacity. - Build dashboards, automation, and reporting systems that provide clear visibility into TaaS capacity, performance, and business outcomes. Qualifications - Strong software engineering background with experience building systems, tooling, automation, or infrastructure platforms. - Experience working across compute infrastructure, distributed systems, performance engineering, or production operations. - Ability to reason about token throughput, utilization, benchmarking, infrastructure efficiency, and workload performance. - Comfortable integrating external systems or partner environments into internal infrastructure stacks. - Strong analytical and debugging skills across hardware, networking, software, and operational domains. Preferred Skills - Experience with GPU clusters, AI infrastructure, performance benchmarking, or workload optimization. - Familiarity with model porting, inference/training workloads, token economics, or compute efficiency analysis. - Experience building monitoring systems for billing, usage, SLAs, utilization, or infrastructure reliability. - Background in systems engineering, infrastructure software, observability, distributed systems, or platform engineering. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers:

About the Team The Intelligence and Investigations team seeks to rapidly detect and disrupt abuse in AI technologies to ensure their safe use. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits all of humanity. About the Role As an Intelligence Systems Engineer, you’ll be focused on advancing our Intelligence & Investigations efforts at OpenAI, ensuring the safe and responsible use of AI across our products and services. We are seeking a self-starter to prototype, develop, and maintain new tools and processes that integrate OpenAI’s models and infrastructure to enable internal teams to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. You will be a crucial technical bridge between our data scientists and subject matter experts and technical teams like Platform Integrity, Safety Systems, and Research by leading the development of innovative tools and processes that bolster goals in scaled collections, investigations, and analysis. The ideal candidate has strong analytical and data skills, with a background in both prototyping and building scalable systems that can swiftly detect emerging threats, process vast amounts of information, and deliver insights to stakeholders. We value professionals with outstanding communication skills, a commitment to continuous learning, and who are dedicated to promoting the responsible use of AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Prototype, build, and maintain at-scale intelligence systems that detect, triage, and monitor targeted signals from both open-source and internal data - Analyze requirements and deliver end-to-end solutions that address complex intelligence challenges while ensuring code quality and scalability - Be a crucial technical bridge between our Intelligence needs and technical teams like Platform Integrity, Safety Systems, and Research - Contribute to shaping the team’s technical strategy and design user interfaces for non-technical investigators and analysts - Prototype new applications to automate team workflows and route leads - Report on scaled impact using advanced data analysis and visualization products - Work closely with internal stakeholders and address their technical intelligence needs You might thrive in this role if you have / are: - Experience in engineering and project management, ideally with a focus on security, intelligence, or data analysis products. - Strong technical background and proven track record of building and maintaining systems that enable users to make sense of large, open-domain datasets, fight abuse, and inform high-stakes decisions. - Proficiency in data analysis, SQL / Python, and application of novel AI techniques for problem-solving. - Demonstrated ability to leverage cross-functional teams, manage complex product ecosystems, and deliver results in a fast-paced and sometimes ambiguous environment. - Strong belief in & passion for the value of AI in enabling humans to better understand the complexity of the world About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: - Build and maintain automation systems for provisioning and managing server fleets. - Develop tools to monitor server health, performance, and lifecycle events. - Collaborate with clusters, networking, and infrastructure teams. - Partner with external operators to ensure a high level of quality. - Identify and fix performance bottlenecks and inefficiencies. - Continuously improve automation to reduce manual work. You might thrive in this role if you have: - Experience managing large-scale server environments. - A balance of strengths in building and operationalizing. - Proficiency in Python, Go, or similar languages. - Strong Linux, networking, and server hardware knowledge. - Comfort digging into noisy data with SQL, PromQL, and Pandas or any other tool. Prior hardware expertise is not required for this role. Bonus Skills: - Experience with low level details of hardware components, protocols, and associated Linux tooling (e.g., PCIe, Infiniband, networking, power management, kernel perf tuning) - Knowledge of hardware management protocols (e.g., IPMI, Redfish). - High-performance computing (HPC) or distributed systems experience. - Prior experience developing, managing, or designing hardware. - Familiarity with monitoring tools (e.g., Prometheus, Grafana). About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction record

About the Team The Cybersecurity Products team builds products at the frontier of AI and cybersecurity. Our work includes Codex Security and related cyber products that turn advances in model capability into dependable tools for defenders. We help teams find, validate, and remediate vulnerabilities, continuously improve the security of software, and test AI-powered applications before they reach production. About the Role As a Full Stack Software Engineer, you will build the product experiences and systems that make AI-powered security useful in real engineering environments. You will work across web surfaces, APIs, orchestration, data models, and integrations to help security and engineering teams move from a codebase or application to evidence-backed findings, prioritized remediation, and revalidation. You will collaborate closely with product engineers, security researchers, and customer-facing teams. The work spans fast-moving product development and hard systems problems: long-running workflows, large repositories, sensitive data, reliability, observability, and a high bar for earning user trust. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Build end-to-end workflows for vulnerability discovery, security scanning, red teaming, findings review, remediation, and reruns. - Design and operate backend services for long-running security work, including APIs, asynchronous orchestration, durable state, and integrations with developer workflows. - Make complex security results actionable through clear product surfaces, strong evidence, thoughtful prioritization, and reliable reporting. - Partner with security researchers, product teams, and users to evaluate quality, reduce noise, improve coverage, and ship safely. You might thrive in this role if you: - Have experience shipping production full-stack products across modern web frontends and backend services. - Can design clear APIs and data models, reason about asynchronous systems, and diagnose reliability or performance problems. - Care about building products that experts trust while making sophisticated workflows usable for a broader set of engineers. - Bring strong judgment around privacy, security, and correctness. Application-security or cybersecurity experience is helpful, but not required. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of emplo

ABOUT THE TEAM Training Runtime designs the core distributed runtime that powers everything from early research experiments to frontier-scale model runs. We work on building robust, scalable, high performance components to support our distributed training workloads. Our priorities are to maximize the productivity of our researchers and our hardware, with the goal of accelerating progress towards AGI. Within Training Runtime, the Process Management team develops the distributed OS responsible for launching, coordinating, and supervising the large numbers of processes that make up modern training workloads. Our runtime sits beneath training frameworks and on top of research infrastructure, ensuring jobs run reliably across massive clusters while maintaining performance, stability, and observability. Success for us is measured by both system reliability and researcher velocity - enabling ideas to scale from experiments to production training runs. ABOUT THE ROLE As a Training Runtime: Process Management Engineer, you will work on the software that ties thousands of computers together and exposes them as a unified system. This system has to serve individual researchers running multiple parallel experiments, as well as our largest training runs spanning 100’s of thousands and even millions of machines and accelerators. This requires easy to use, introspectable systems that can promote a fast debugging and development cycle, as well as relentless optimization for scale while maintaining stability and performance throughout. You will work primarily in Rust, building high-performance asynchronous systems with a strong emphasis on performance, correctness, and scalability. Working at this scale and at the frontier of AI development poses novel challenges. Out-of-the-box approaches often don’t work. The problems you will be working on are highly ambiguous and require strong design judgment as well as proficient execution to advance the state of our infrastructure. We’re looking for people who love optimizing an end-to-end platform, understanding high-performance architectures to maximize both local and distributed performance across our supercomputers. We’re looking for engineers excited by the rapid pace of responding to the dynamic and evolving needs of our training runtime and compute stack. This role is based in London, UK. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Work across our Python and Rust stack - Design, build, and maintain software to orchestrate and monitor machine learning workloads on our largest supercomputers - Profile and optimize our software stack to support computation orchestration at frontier scale - Improve reliability, observability, and fault tolerance for long-running jobs - Debug complex distributed systems issues across large clusters - Respond to the changing shapes and needs of the ML systems to enable our researchers YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have experience developing distributed systems (not just operating them) - Enjoy understanding how large systems behave and fail at scale - Care deeply about performance, correctness, and reliability - Have strong software engineering skills and are proficient in Python and Rust or another systems programming language (e.g. C++) - Have solid Linux knowledge, and are comfortable with systems-level debugging, performance analysis, and memory profiling - Are comfortable and experienced working and developing asynchronous and concurrent systems - Like high-ownership environments with light process and strong engineering agency About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety

ABOUT THE TEAM OpenAI’s Alignment team works to ensure that increasingly capable AI systems reliably follow human intent, avoid catastrophic behavior, and remain controllable, auditable, and safe as capabilities scale. The team is fast-moving: priorities change as evidence, risks, and organizational needs change. We need people who can help execute important alignment and safety priorities that don’t otherwise have an owner. ABOUT THE ROLE We are looking for a Research Program Manager for the Alignment team. You should expect to move between big, ambiguous questions and very concrete execution: writing a crisp project plan, tracking owners, chasing a decision, running a process, organizing a meeting, helping unblock a researcher, or picking up the operational work nobody else has time to do. OpenAI is a continuously evolving place, and this role will evolve with it. Some projects will be highly visible and strategic; others will be small, practical, or unglamorous. The common thread is doing whatever needs to be done in service of alignment/safety at OpenAI. If you want a role where no work is below you but where scope can expand quickly, and where good judgment and follow-through matter as much as title or function, this may be a strong fit. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Own 2-4 ambiguous alignment special projects at a time, from problem definition through execution and follow-through. - Turn fuzzy goals into clear plans, milestones, owners, decision points, and operating rhythms. - Drive practical execution across research, engineering, policy, product, legal, communications, recruiting, and external collaborators as needed. - Create and maintain lightweight systems that help alignment work scale, such as project trackers, decision memos, operating processes, review loops, and recurring coordination forums. - Synthesize technical and organizational context into clear written artifacts that help leaders and researchers make decisions quickly. - Map the alignment and AI safety community: understand who is working on what, what people care about, where OpenAI can help, and which collaborations are worth pursuing. - Run internal or external programs when they matter for alignment, including events, fellowships, publishing workflows, community programs, research collaborations, and governance processes. - Do the small work that makes the big work possible: schedule the meeting, write the first draft, clean up the tracker, follow up on the loose end, and make sure the thing actually ships. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have 4+ years of experience in research program management, technical program management, operations, chief-of-staff work, partnerships, recruiting, or related roles in fast-moving environments. - Can take a loosely scoped problem, figure out what matters, decide what needs to happen next, and drive it without waiting for detailed instructions. - Are low-ego and execution-oriented: you are equally willing to shape a strategy, write the memo, run the meeting, and handle the logistics. - Write clearly and concisely, especially when translating messy technical or organizational context into decision-ready documents. - Can build trust with researchers and technical teams while also keeping work moving across operational and cross-functional partners. - Are comfortable with ambiguity, confidentiality, changing priorities, and holding several workstreams in your head at once. - Have familiarity with the AI safety or alignment ecosystem, or can get up to speed quickly enough to know who to talk to and what the community cares about. STRONG CANDIDATES MAY ALSO HAVE: - Experience working directly with AI safety, machine learning, or research teams. - Experience building a new program, process, community effort, or function from scratch. - Experience with fellowships, re

About the Team The Solutions Engineering team is made up of trusted technical advisors who help organizations adopt OpenAI’s technology safely, effectively, and responsibly. We partner closely with customers, Sales, Product, Engineering, and Security to translate frontier AI capabilities into practical workflows that create real-world impact. Cybersecurity is one of the most urgent areas where AI can help. As frontier models become more capable at reasoning over code, logs, infrastructure, and security evidence, organizations need guidance on how to evaluate, validate, and deploy these systems safely. Our goal is to help customers move from identifying risks to implementing solutions. About the Role We are committed to bringing together people from diverse backgrounds and perspectives who are excited to help build and deploy safe, useful AI. We are seeking a solutions engineer to partner with our Enterprise customers and ensure they achieve tangible business value from our models through the OpenAI suite of products. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. You will work closely with Enterprise Sales, Security, and Product teams. We are looking for a Field Security Specialist to help security leaders and hands-on practitioners understand how OpenAI models, APIs, Codex, and agentic workflows can be applied to real cybersecurity use cases. This is a customer-facing specialist role for someone who can move fluidly between CISO-level conversations, practitioner-level technical depth, and hands-on solution design. You’ll help customers evaluate OpenAI for workflows like secure code review, vulnerability triage, threat modeling, remediation, SOC workflows, detection engineering, and security validation. You will be the field’s cyber expert: shaping discovery, demos, pilots, reference architectures, implementation guidance, and repeatable assets that help customers adopt AI safely in high-stakes security environments. In this role, you will: - Lead cyber workflow discovery with customers across AppSec, DevSecOps, vulnerability management, SOC/IR, detection engineering, red team, cloud security, and GRC automation. - Build and deliver customer-facing demos, workshops, proofs of concept, and reference architectures for AI-enabled security workflows. - Scope pilots with clear success criteria, data requirements, integrations, evaluation methods, safety boundaries, and human approval points. - Advise customers on safe implementation patterns, including tool/function calling, structured outputs, sandboxing, data handling, guardrails, auditability, and approval-gated side effects. - Translate between executive buyers and hands-on security practitioners, helping each audience understand value, risk, and practical next steps. - Create reusable field assets such as demo narratives, playbooks, FAQs, objection handling, qualification guides, assessment templates, and competitive positioning. - Bring recurring customer requirements, product gaps, blockers, and high-value cyber workflows back to Product, Engineering, Security, and GTM teams. You might thrive in this role if you: - Have deep practitioner credibility across cybersecurity domains such as application security, cloud security, identity, vulnerability management, secure SDLC, incident response, detection engineering, or attacker tradecraft. - Have worked in a customer-facing, advisory, consulting, solutions engineering, security architecture, or technical field role. - Can build credible demos or prototypes using APIs, Codex, agents, scripts, CLIs, GitHub workflows, CI/CD systems, logs, tickets, scanners, or other common security tooling. - Understand how to design AI workflows with

ABOUT THE TEAM Safety Systems sits at the forefront of OpenAI’s mission to build and deploy safe AGI, ensuring our most capable models can be released responsibly and for the benefit of society. Within Safety Systems, we are building a misalignment research team to focus on the most pressing problems for the future of AGI. Our mandate is to identify, quantify, and understand future AGI misalignment risks far in advance of when they can pose harm. The work of this research taskforce spans four pillars: 1. Worst‑Case Demonstrations – Craft compelling, reality‑anchored demos that reveal how AI systems can go wrong. We focus especially on high importance cases where misaligned AGI could pursue goals at odds with human well being. 2. Adversarial & Frontier Safety Evaluations – Transform those demos into rigorous, repeatable evaluations that measure dangerous capabilities and residual risks. Topics of interest include deceptive behavior, scheming, reward hacking, deception in reasoning, and power-seeking, along with other related areas. 3. System‑Level Stress Testing – Build automated infrastructure to probe entire product stacks, assessing end‑to‑end robustness under extreme conditions. We treat misalignment as an evolving adversary, escalating tests until we find breaking points even as systems continue to improve. 4. Alignment Stress‑Testing Research – Investigate why mitigations break, publishing insights that shape strategy and next‑generation safeguards. We collaborate with other labs when useful and actively share misalignment findings to accelerate collective progress. About the Role We are seeking a Senior Researcher who is passionate about red‑teaming and AI safety. In this role you will design and execute cutting‑edge attacks, build adversarial evaluations, and advance our understanding of how safety measures can fail—and how to fix them. Your insights will directly influence OpenAI’s product launches and long‑term safety roadmap. IN THIS ROLE, YOU WILL - Design and implement worst‑case demonstrations that make AGI alignment risks concrete for stakeholders, focused on high stakes use cases described above. - Develop adversarial and system‑level evaluations grounded in those demonstrations, driving adoption across OpenAI. - Create automated tools and infrastructure to scale automated red‑teaming and stress testing. - Conduct research on failure modes of alignment techniques and propose improvements. - Publish influential internal or external papers that shift safety strategy or industry practice. We aim to concretely reduce existential AI risk. - Partner with engineering, research, policy, and legal teams to integrate findings into product safeguards and governance processes. - Mentor engineers and researchers, fostering a culture of rigorous, impact‑oriented safety work. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Already are thinking about these problems night and day, and share our mission to build safe, universally beneficial AGI and align with the OpenAI Charter. - Have 4+ years of experience in AI red‑teaming, security research, adversarial ML, or related safety fields. - Possess a strong research track record—publications, open‑source projects, or high‑impact internal work—demonstrating creativity in uncovering and exploiting system weaknesses. - Are fluent in modern ML / AI techniques and comfortable hacking on large‑scale codebases and evaluation infrastructure. - Communicate clearly with both technical and non‑technical audiences, translating complex findings into actionable recommendations. - Enjoy collaboration and can drive cross‑functional projects that span research, engineering, and policy. - Hold a Ph.D., master’s degree, or equivalent experience in computer science, machine learning, security, or a related discipline (nice to have but not required). About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push t

About the Team: Our Safety Systems https://openai.com/safety/safety-systems org ensures that OpenAI’s most capable models can be responsibly developed and deployed. We build evaluations, safeguards, and safety frameworks that help our models behave as intended in real-world settings. About the Role: We are seeking a Researcher in Privacy-Preserving Safety to help design and build the next generation of privacy-preserving safety systems for frontier AI models. This role sits at the intersection of AI safety, security, and privacy, with a focus on developing auditable, privacy-first mechanisms that enable robust harm detection and mitigation without exposing sensitive user data. You will help define and operationalize frameworks for identifying and addressing frontier risks (e.g., bioweapon instructions, malware creation, suicide/self-harm risks, jailbreaks), while ensuring that privacy guarantees remain intact—even under adversarial conditions. This role is central to our long-term goal of scaling our automated privacy-preserving safety systems to mitigate potential harms while minimizing human review. You’ll work on foundational problems such as privacy-preserving monitoring, algorithmic auditing, secure enclaves, and adversarially robust safety enforcement protocols, helping ensure that safety systems scale without compromising user trust. In this role, you will: - Design and implement privacy-first architectures for detecting and mitigating harmful model behaviors. - Build frameworks for auditable private identification of high-risk content (jailbreaks, cyber threats, or weaponization instructions). - Develop strict, auditable mechanisms triggered only by harm signals. - Drive the development of automated safety systems that preserve privacy at every level. You might thrive in this role if you: - Are a researcher with deep interest in privacy, security, and AI safety, motivated by building systems that are both trustworthy and effective at scale. - Hold a PhD or equivalent experience in Computer Science, Cryptography, Security, Machine Learning, or related fields - Have the ability to translate ambiguous problem spaces into formal frameworks and deployable systems - Demonstrate profiency in one or more of: - Privacy-preserving computation (e.g., secure enclaves, MPC, differential privacy) - Security and adversarial systems - Machine learning safety or alignment - Experience designing robust systems under adversarial threat models - Have experience with AI safety, jailbreak detection, or model alignment - Are familiar with privacy-preserving machine learning techniques, algorithmic auditing and/or secure system design About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidat

ABOUT THE TEAM OpenAI's mission is to ensure that artificial general intelligence benefits all of humanity. The Consumer Devices team is building a new generation of AI-powered products that seamlessly integrate hardware and software to create intuitive, transformative experiences. We bring together experts across embedded systems, machine learning, hardware, design, and product engineering to develop products at the intersection of AI and consumer technology. ABOUT THE ROLE OpenAI is seeking a System Performance Engineer to profile, benchmark, and optimize performance across our embedded hardware products. In this role, you will work across operating systems, applications, camera and vision, graphics, and platform teams to define product KPIs, build performance tooling, and drive optimizations from early lab characterization through product launch and real-world usage. You will help establish the performance standards that shape the user experience of our products, ensuring they remain responsive, efficient, and reliable throughout their lifecycle. This role requires deep expertise in embedded or high-performance systems, strong operating systems fundamentals, and hands-on experience debugging under tight latency, power, and memory constraints. This role is based in San Francisco, CA. We use a hybrid work model of four days per week in the office and one day working remotely. Relocation assistance is available for new hires. IN THIS ROLE, YOU WILL: - Develop system performance benchmarks, methodologies, and policies to evaluate end-to-end product behavior. - Profile and analyze performance across key product use cases and workloads using custom and industry-standard profiling tools. - Partner closely with engineering teams to identify bottlenecks and drive performance optimizations across the software stack. - Define high-level product KPIs and establish measurement frameworks to measure launch readiness and monitor performance throughout the product lifecycle. - Measure, report, and track metrics including system responsiveness, memory utilization, cold boot performance, long-term stability, and behavior under constrained conditions such as thermal limits and low battery states. - Investigate field performance regressions and drive issues to resolution using data-driven analysis. YOU MIGHT THRIVE IN THIS ROLE IF YOU HAVE: - Deep experience shipping embedded or high-performance systems on Linux, Android, or iOS devices. - Strong proficiency in C/C++, Python, or Rust, with exceptional operating systems fundamentals, including process management, IPC, drivers, interrupts, power management, media frameworks, graphics, filesystems, and networking. - A proven track record shipping real-time systems operating under tight latency, power, and memory constraints. - Expertise with profiling and debugging tools such as Perfetto, GDB, LLDB, perf, ftrace, or Instruments. - Experience building instrumentation, analytics, and performance tuning frameworks. PREFERRED QUALIFICATIONS - Familiarity with statistics, experimentation methodologies, or data science concepts. - Experience collaborating cross-functionally with embedded software, systems, camera and vision, audio, graphics, applications, and hardware teams. - Experience defining product KPIs, benchmarking methodologies, and launch readiness metrics for hardware products. - Experience investigating field performance regressions and driving fixes through cross-functional collaboration. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectr

About The Team The Alignment Training team studies how frontier models acquire durable behavioral tendencies across the training stack. We work on identifying which behaviors can be shaped through pre-training, mid-training, and post-training; building the data, objectives, and evaluations needed to influence them; and determining whether the resulting behavior reflects a general learned tendency or a narrow artifact of the training distribution. Our work spans synthetic data, pre-training, mid-training, post-training, model behavior, and evaluation. We study how models learn to interpret intent, follow instructions, reason through tasks, express uncertainty, act honestly, and remain reliable under new conditions. The goal is to make desirable tendencies emerge early, strengthen throughout training, and appear robustly in deployed systems. About The Role We’re looking for a senior researcher with exceptional technical depth in large-scale model training, synthetic data, or evaluation who is excited to study how training choices shape aligned behavior in frontier models. You will help shape the research agenda for alignment training: defining the behaviors we want models to learn, designing data and training interventions to teach them, and building the evaluation loops needed to tell whether those behaviors are broad, robust, and durable. The strongest candidates will be able to move from an ambiguous behavioral question to a concrete experimental program: formulate the hypothesis, design the intervention, build the pipeline, run the experiment, and decide whether the result is real. This role is especially well suited for someone who wants to work close to the core model training loop, where choices about data, objectives, and evaluation directly shape how aligned deployed systems are. In this role, you'll: - Develop synthetic data methods that teach models higher-level behavioral tendencies, such as understanding user intent, following instructions reliably, reasoning clearly, being honest, and acting consistently with intended goals and constraints. - Study how pre-training, mid-training, and post-training each shape downstream model behavior, and which interventions are best applied at which stage. - Build evaluation loops that connect model behavior back to training data and training objectives, so the team can iterate faster and with clearer signal. - Design reusable data generation and filtering pipelines that improve the quality, diversity, and robustness of training data. - Create experiments that distinguish durable learned behavior from benchmark gains, distribution-specific effects, or evaluation artifacts. - Collaborate across pre-training, post-training, alignment, and product-facing teams to translate research insights into better model behavior. - Help define the research agenda for alignment training: which behaviors should remain invariant across settings, which should adapt, and how to measure whether models have learned an underlying principle rather than a surface pattern. You might thrive in this role if you: - Have a strong record of technically excellent work in large-scale ML, especially in pre-training, post-training, synthetic data, model evaluation, or training infrastructure. - Are comfortable designing experiments where the signal is subtle, noisy, or indirect. - Can move between research taste and engineering execution: forming hypotheses, building pipelines, running experiments, analyzing results, and turning findings into the next iteration. - Have unusually good judgment about which research questions are worth pursuing and which signals are strong enough to trust. - Care about making models more useful, honest, steerable, and reliable for real users. - Are excited by alignment problems, even if you have not worked in alignment before. - Communicate clearly across research, engineering, and product contexts. - Prefer practical, evidence-driven work grounded in experiments. About OpenAI OpenAI

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Senior Software Engineer, ML Systems & Training Infrastructure, you will be a deeply hands-on engineering force multiplier for the robotics team. You will help keep the training framework and surrounding infrastructure healthy, review and improve code quickly, debug failures across ML systems and infrastructure, and unblock researchers and engineers when the path from idea to working training job gets rough. We’re looking for people who love writing, reading, reviewing, and fixing code; who can get productive quickly in unfamiliar systems; and who bring strong practical judgment without a lot of ego or process overhead. This role will be based in San Francisco, CA and be expected in office 5 days per week and offer relocation assistance to new employees. In this role, you will: - Review, improve, and clean up code across training frameworks and adjacent infrastructure. - Identify risky or low-quality changes before they land, and raise the code quality bar without slowing the team down. - Debug issues across ML training systems, GPUs, clusters, networking, and related infrastructure. - Help researchers and engineers unblock broken training jobs, flaky workflows, and brittle internal tooling. - Improve the reliability, maintainability, and usability of the robotics team’s training framework. - Move quickly on practical engineering problems that directly affect team velocity. You might thrive in this role if you: - Have strong software engineering fundamentals and excellent code review judgment. - Have experience with ML systems, training frameworks, GPUs, distributed systems, infrastructure, or similarly complex technical environments. - Read and debug unfamiliar codebases quickly, and enjoy getting to root cause. - Ship high-quality code with strong velocity and pragmatic judgment. - Are low-ego, responsive, and motivated by helping researchers and engineers move faster. - Prefer being a highly effective hands-on IC over driving broad process-heavy initiatives. - Have experience reviewing messy, fast-moving, or AI-generated codebases. Compensation Range: $295K - $380K USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direc

ABOUT THE TEAM We’re hiring a Developer Productivity engineer to support OpenAI’s Inference Runtime teams. These teams own the systems responsible for serving models reliably, efficiently, and safely across Codex, ChatGPT, API, and internal research workloads. We’re hiring a Developer Productivity Engineer to help scale the engineering systems, safeguards, and developer workflows that enable our teams to move quickly without compromising reliability or performance. This role sits at the intersection of developer experience, CI/CD infrastructure, release engineering, production readiness, and inference systems reliability. You’ll work on the tooling and operational foundations that support model launches, inference optimizations, cloud provider integrations, and large-scale deployments across a rapidly evolving inference stack. ABOUT THE ROLE We’re looking for an autonomous, high-ownership engineer who cares deeply about making other engineers faster, safer, and more confident. A major focus of this role will be improving the tooling and infrastructure around deploy gates for inference engine images. These systems help ensure that every image released to production and research is correct, numerically sound, free of regressions, and performant across key metrics like time-to-first-token (TTFT) and time-between-tokens (TBT). You’ll help harden the systems that catch issues before they reach production, reduce noise from flaky or infrastructure-related test failures, and improve automation around triage, ownership, debugging, and escalation when failures occur. You’ll also work on improving observability, rollout safety, release automation, and developer self-service tooling across a rapidly evolving inference stack. This is not generic internal tools work. The systems you build directly impact OpenAI’s ability to support new model launches, safely ship inference optimizations to the world, onboard new infrastructure providers, and operate one of the largest and most performance-sensitive inference platforms in the world. In this role, you will: - Improve systems that ensure inference engine releases are correct, performant, and regression-free by evolving tooling and infrastructure for deploy gate validation - Bring rigor to release, validation, branching, and deployment processes across the inference stack - Improve canary, async, and large-scale validation workflows for inference systems - Harden CI, testing, and validation infrastructure so failures are actionable and trustworthy - Reduce noisy or flaky failures caused by infrastructure instability, GPU scheduling, or test environment issues - Build automation for failure triage, ownership detection, debugging, and escalation - Partner closely with inference teams, research developer productivity, engine acceleration, and infrastructure teams to improve release quality and rollout safety - Reduce developer friction in testing, debugging, and release workflows so engineers can move faster with confidence YOU MIGHT THRIVE IN THIS ROLE IF: - You have strong experience with CI/CD systems, testing infrastructure, release tooling, developer productivity, or large-scale build and validation systems - You are excited by high-impact infrastructure where small regressions in correctness, latency, or reliability meaningfully affect production systems - You care about building systems engineers can trust, not just systems that technically function - You have strong developer empathy and enjoy improving workflows, reducing friction, and making engineers more effective - You demonstrate high ownership and proactively identify problems, drive improvements, and follow issues through resolution - You are comfortable working in Python-heavy environments and debugging complex distributed systems - You enjoy building automation that reduces manual triage, improves signal quality, and scales operational effectiveness - You are comfortable operating in ambiguous areas without a fully predefined ro

About the Team The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. About the Role As a Quantitative Intelligence Analyst, you will focus on discovering novel and emerging risks in complex human–AI systems before they are well-defined, measurable, or widely understood. You will use deep subject matter expertise and quantitative tooling to surface weak, early, and unconventional risk signals. You will build analytic models that explain how harms could emerge and translate ambiguous patterns into structured, data-driven insight. Your work will help identify potential gaps in policy or coverage and operationalize previously unmeasured problems into signals that can support detection, mitigation, and planning downstream. You will develop analytical frameworks that map how new risks form, evolve, and propagate as products change, policies shift, and external events unfold. Your analyses will directly inform strategic risk prioritization and planning across the company, with regular visibility through strategic risk products. This role is based in office (hybrid, 3 days/week). Relocation support is available In this role, you will: - Discover and define new quantitative risk signals where no established metrics exist, using subject matter expertise to surface early, weak, or unconventional indicators - Translate complex trust and safety challenges into measurable signals that can be tracked and stress-tested over time - Develop upstream early-warning and signal frameworks that inform downstream detection and mitigation efforts - Analyze risk trends to assess the underlying drivers and causal factors behind those changes - Conduct data mining and statistical modeling to understand how risks originate, evolve, and propagate across systems - Design adversarial scenarios, and quantitative stress tests to assess exposure, coverage gaps, and vulnerabilities - Produce clear data-driven briefs to support risk prioritization, contingency planning, and strategic risk products across teams You might thrive in this role if you: - Have 3+ years of experience in quantitative intelligence analysis, trust & safety, security analysis, or risk-focused research - Are comfortable working on complex trust and safety domains such as child safety, violent activities, self-harm, or similar high-stakes risk areas - Familiarity with data mining, statistical modeling, and supervised learning methods - Understand how to monitor signals or models for data drift, behavioral adaptation, or performance degradation over time, and can diagnose likely causes - Experience in operationalizing adversarial or strategic risk behaviors, including through red-team exercises, agent-based modeling, or structured scenario analyses - Comfortable working with Python and SQL - Nice to have: Experience with quantitative stress testing or Monte Carlo simulations to assess uncertainty and tail risk About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at it

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: - Build and maintain automation systems for provisioning and managing server fleets. - Develop tools to monitor server health, performance, and lifecycle events. - Collaborate with clusters, networking, and infrastructure teams. - Partner with external operators to ensure a high level of quality. - Identify and fix performance bottlenecks and inefficiencies. - Continuously improve automation to reduce manual work. You might thrive in this role if you have: - Experience managing large-scale server environments. - A balance of strengths in building and operationalizing. - Proficiency in Python, Go, or similar languages. - Strong Linux, networking, and server hardware knowledge. - Comfort digging into noisy data with SQL, PromQL, and Pandas or any other tool. Prior hardware expertise is not required for this role. Bonus Skills: - Experience with low level details of hardware components, protocols, and associated Linux tooling (e.g., PCIe, Infiniband, networking, power management, kernel perf tuning) - Knowledge of hardware management protocols (e.g., IPMI, Redfish). - High-performance computing (HPC) or distributed systems experience. - Prior experience developing, managing, or designing hardware. - Familiarity with monitoring tools (e.g., Prometheus, Grafana). About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for

About the Team OpenAI’s People team is committed to hiring, engaging, and supporting world-class talent to help safely build and deploy universally beneficial Artificial General Intelligence (AGI). The Recruiting Optimizations Manager is responsible for building and strengthening the systems, workflows, and operational infrastructure that make hiring at OpenAI fast, rigorous, and scalable. This role partners across recruiting, systems, and people teams to ensure recruiting foundations are efficient, reliable, auditable, and built to scale as OpenAI continues to grow rapidly and globally. This role leads Recruiting Operations optimization efforts across workflow design, operational automation, systems enablement, and scalable service operations. About the Role This role is focused on the systems and operational backbone of recruiting. The Recruiting Operations Manager will lead work across recruiting systems, workflow design, automation, process optimization, and data integrity to improve how hiring runs at scale. This role will translate business needs into durable operational solutions, drive improvements across the recruiting technology stack, and identify opportunities to reduce manual work through better tooling, automation, and process design. The right person will combine strong people management with systems thinking, operational rigor, and a practical approach to scaling high-quality recruiting infrastructure. This role is based in San Francisco, CA. We are not considering remote candidates at this time. In this role, you will: - Lead and develop a high-performing Recruiting Operations team, setting clear expectations, building strong judgment, and supporting career growth. - Own and improve the operational systems and workflows that underpin recruiting, with a focus on scalability, reliability, and efficiency. - Design, implement, and continuously optimize automations across recruiting workflows, approvals, data quality checks, reporting processes, and systems handoffs. - Identify manual, repetitive, or error-prone work and convert it into streamlined, governed, and scalable processes. - Partner with Recruiting, People Systems, and cross-functional stakeholders to prioritize and deliver tooling improvements, workflow redesigns, and operational enhancements. - Support the evolution of the recruiting technology stack by defining requirements, evaluating solutions, improving integrations, and driving adoption of new processes and tools. - Use data to monitor process health, identify bottlenecks, and drive continuous improvement across operational performance and system effectiveness. - Raise the bar on data accuracy, systems hygiene, documentation, and process discipline across recruiting operations. - Act as an escalation point for complex operational issues, using structured problem-solving and sound judgment to resolve root causes. - Contribute to an AI-enabled roadmap for recruiting operations, with a focus on practical automation, usability, governance, and measurable impact. You might thrive in this role if: - You care deeply about building reliable systems and operational foundations that scale. - You naturally look for ways to simplify, automate, and optimize workflows rather than maintain manual workarounds. - You are comfortable operating in ambiguity and can bring structure to evolving processes and systems. - You know how to lead a team through both day-to-day execution and longer-term systems improvement. - You bring strong judgment and know when to escalate risks, challenge unclear requirements, or tighten a process that is not holding up. - You balance speed with rigor and understand that operational quality is a trust function. - You can zoom out to design scalable workflows and zoom in to debug process failures, systems gaps, or data issues. - You are credible with stakeholders and able to build strong working relationships across recruiting, systems, analytics, finance, legal, and IT. What We’re Looking

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: - Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. - Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. - Develop automation and detection tooling to continuously identify and mitigate risks in large-scale cloud and on-prem environments. - Drive high-impact initiatives such as line-speed encryption, machine identity, and network isolation, continuously raising the security bar for emerging AI workloads. - Lead or participate in design reviews and threat models to ensure new systems launch with strong security foundations and operational excellence. You will thrive in this role if you have: - Strong software engineering skills in languages such as Python, Go, Rust, or C/C++, with a track record of shipping and operating high-reliability distributed services. - Experience building or operating critical security infrastructure (e.g., auth services, service-to-service proxies, certificate or key-management systems). - Deep understanding of security principles, best practices, and common vulnerabilities. - Expertise in securing large-scale cloud platforms (e.g., Azure, AWS, GCP), including multi-cloud networks and cloud-agnostic system design. - Familiarity with container and orchestration security (Kubernetes, service meshes) and modern authentication/authorization standards (OIDC, mTLS, SPIFFE/SPIRE). - A proactive mindset, with the ability to identify and address security gaps or inefficiencies through automation and tooling. - A track record of delivering scalable solutions and driving impactful changes across infrastructure in real-world projects. - Strong analytical and problem-solving skills, with an ability to think critically and objectively assess security risks. - Excellent communication skills, with the ability to convey complex security concepts to technical and non-technical stakeholders. - Excitement about collaborating with cross-functional teams to build secure, reliable systems that scale globally. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek

ABOUT THE TEAM The Foundations team focuses on how model behavior changes as we scale models, data, and compute. The team studies the interactions between model architecture, optimization, and training data, and uses those insights to guide how new models are designed and trained. ABOUT THE ROLE In this role, you will build the systems that enable advanced AI models to run efficiently at scale. You will operate at the intersection of model research and systems engineering, translating new architectural ideas into high-performance inference systems that surface real tradeoffs in performance, memory, and scalability. Your work will directly influence how models are designed, evaluated, and iterated on across the research organization. By developing and evolving high-performance inference infrastructure, you will enable researchers to explore new ideas with a clear understanding of their computational and systems implications. This is not a product-serving role. Instead, it is a research-enabling systems role focused on performance, correctness, and realism - ensuring that AI research is grounded in what can actually scale. IN THIS ROLE, YOU WILL: - Design and build high-performance inference runtimes for large-scale AI models, with a focus on efficiency, reliability, and scalability. - Own and optimize core execution paths, including model execution, memory management, batching, and scheduling. - Develop and improve distributed inference across multiple GPUs, including parallelism strategies, communication patterns, and runtime coordination. - Implement and optimize inference-critical operators and kernels informed by real-world workloads. - Partner closely with research teams to ensure new model architectures are supported accurately and efficiently in inference systems. - Diagnose and resolve performance bottlenecks through profiling, benchmarking, and low-level debugging. - Contribute to observability, correctness, and reliability of large-scale AI systems. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have experience building production inference systems, not just training or running models. - Are comfortable with GPU-centric performance engineering, including memory behavior and latency/throughput tradeoffs. - Have worked on multi-GPU or distributed systems involving batching, scheduling, or runtime coordination. - Can reason end-to-end about inference pipelines, from request handling through execution and output streaming. - Are able to understand research ideas and implement them within real system and performance constraints. - Enjoy solving hard, ambiguous systems problems that only emerge at scale. - Prefer hands-on technical ownership and execution over abstract design work. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employer

About the Team Security is foundational to OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security organization protects OpenAI’s technology, people, and products by building and operating deeply technical systems that must work reliably at massive scale. Our work underpins OpenAI’s commitments around safety, privacy, and security across research, products, and emerging platforms. The Host Assurance team exists to make bare metal a dependable, scalable foundation for OpenAI: secure by default, verifiable in practice, and resilient across providers and operating models. We operate at the trust boundary between physical hardware and cloud-scale orchestration, ensuring that hosts are eligible to safely run workloads with predictable security properties and auditability. About the Role OpenAI is seeking a Security Engineer, Host Assurance to help build the trust foundations for bare-metal platforms across OpenAI’s global infrastructure. This is a deeply hands-on engineering role for a builder who can design, implement, and operate the core security infrastructure that establishes trust in hardware platforms before they are eligible to run workloads. Success in this role requires strong technical judgment, the ability to work comfortably at low levels of the stack, and a practical mindset for building systems that are secure, reliable, and usable in fast-moving production environments. The systems you build will sit on the critical path of OpenAI’s frontier infrastructure investments and will directly shape how large amounts of compute are brought online - securely, responsibly, and at global scale - underpinning long-lived commitments around privacy, security, and reliability. You will partner closely with infrastructure, research, and confidential computing initiatives—including novel hardware platforms and emerging deployment models– to make the secure path the easiest path. This role is well suited for engineers who enjoy working across trust services, operating systems, hardware and firmware validation, and infrastructure security, and who are excited by ambiguous, high-impact problems at the boundary of hardware and large-scale systems. In this role, you will: - Design, build, and operate components of the Host Assurance platform that establish trust in bare-metal hosts before they are eligible for production use. - Help ensure hosts are verifiably trustworthy from delivery and installation through secure bootstrap and readiness to join orchestration systems. - Build and improve systems such as machine identity, certificate issuance and enrollment, HSM-backed or key-management-backed trust services, host attestation, measurement, and baseline verification tooling. - Validate delivered hardware and firmware against vendor claims and continuously detect and manage drift over time. - Eliminate insecure bootstrap patterns while preserving deployment throughput and operational reliability. Partner with provisioning, fleet, and orchestration teams to deliver paved paths where the secure approach is the easiest approach. - Contribute code, reviews, operational improvements, and design guidance for foundational trust services that must be dependable at scale. - Help define observable, testable security properties for host platforms and improve the telemetry and validation needed to enforce them in practice. - Participate in incident response, debugging, and post-incident improvements for security-critical infrastructure. - Work across different deployment models and provider boundaries while maintaining a consistent bar for host trust outcomes. You might thrive in this role if you: - Have strong software engineering experience building and operating reliable production systems at scale. - Have deep expertise in at least one relevant domain such as PKI, HSMs, machine identity, applied cryptography, secure boot, firmware or hardware security, host attestation, or low-level platform securit

About the Team The GTM (Go-To-Market) Innovation team is an internal powerhouse revolutionizing how we engage customers through groundbreaking applications of our technology. As an incubator, we amplify the impact of Sales, Technical Success, Enablement, and Revenue Operations by deploying our technology at scale. This team applies advanced capabilities to real-world interactions — reshaping conversations with customers, learning from every exchange, and finding novel ways to show the value of our technology. About the Role We’re looking for product mindset software engineers to join the GTM Innovation team. As a product engineer on this team, you’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: - Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts - Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain - Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them - Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems - Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: - Have 4+ years of experience as a software/ML/product engineer working on user-facing systems - Former founder, or early engineer at a startup who built a product from scratch is a plus - Are fluent in Python or JavaScript and comfortable building full-stack applications - Have built or prototyped LLM-powered workflows using the OpenAI API (or similar) - Take initiative, move quickly, and operate with a strong sense of ownership - Enjoy working closely with end users and shaping 0→1 products - Are collaborative, curious, and motivated to make an outsized impact at the frontier of AI About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building an AI powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for Software Engineers who're passionate about blending production-ready platform architecture with new tech and new paradigms. You’ll push the boundaries of OpenAI’s newest technologies to enable interactions and automations that are not only functional, but delightful. We value proactive, customer-centric engineers who can get the foundational details right (data models, architecture, security) in service of enabling great products. In this role, you will: - Own the end-to-end development lifecycle for new platform capabilities and integrations with other systems - Collaborate closely with engineers, data scientists, information systems architects, and internal customers to understand their problems and implement effective solutions - Work with product and research team to share relevant feedback and iterate on applying their latest models About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of pro

ABOUT THE TEAM The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem in close collaboration with our internal and external partners. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. ABOUT THE ROLE We are looking for an AI emerging risks analyst to help us understand potential harms and misuse of AI at the frontier in a time of rapid, sustained change. From known threat actors misusing new technologies to new threats enabled by new technologies, we seek to scan available signals and use strategic foresight methodologies to enable proactive detection and mitigation of frontier AI risks. In this role, you will help to provide strategic-level perspective on a range of evolving risk areas, helping to produce actionable understanding of frontier AI risks relevant to OpenAI’s platforms, surfaces, and broader business interests. Utilizing mixed quantitative and qualitative methodologies, you will spot early warning signs, pull threads on potentially concerning behavior, and turn weak signals into clear, prioritized risk calls. You will focus on upstream ecosystem scanning, competitive benchmarking, and external narrative/risk sense-making. Your work will help to inform cross-functional partners in the protection and safety stacks to guide mitigations that keep users, brands, and communities safe while allowing productive, creative uses of these tools to thrive. IN THIS ROLE, YOU WILL - Map and prioritize emerging risks at the frontier of AI - Build and continuously refine a clear picture of emerging signals and trends that could affect the AI ecosystem through upstream and external scanning. - Design and maintain harm taxonomies that provide foresight and warning about how AI harms and misuse may manifest over the next 0-24 months and beyond. - Contribute to an evergreen frontier risk register and prioritization framework that surfaces the top issues by severity, prevalence, exposure, and trajectory. - Detect and deep dive into emerging abuse patterns - Create comprehensive approaches to horizon scanning, competitive benchmarking, and external narrative/risk sense-making. - Stay current on abuse trends ranging from state actor misuse to criminal activity, drawing from the work of internal organizational and cross-functional partners. - Connect individual incidents into system-level stories about actors, incentives, product design weaknesses, and cross-product spillover–whenever possible spotting these incidents or even hypothesizing them before they hit our surfaces. - Turn analysis into actionable risk intelligence - Translate findings into clear, ranked risk lists and concrete proposals for mitigations that product, safety, and policy teams can execute on. - Work with Global Affairs and Communications teams to share findings in ways that reinforce OpenAI’s role as a leader in the online safety ecosystem. - Track whether mitigation work is landing: follow key indicators, pressure-test assumptions, and push for course corrections when the data demands it. - Build early warning and measurement capabilities - Help define the core metrics and signals that indicate whether fast-evolving AI environments are safe (e.g., key harm prevalence, severity distributions, escalation rates, brand safety issues). - Work with data science and visualization colleagues to shape monitoring views and dashboards that highlight leading indicators and unusual changes from signals spotted off platform to determine whether these are manifesting in user behavior or abuse patte

About the Team Business Systems / Enterprise Platform Technology builds the internal systems, data foundations, workflow infrastructure, and enterprise platforms that help OpenAI operate at scale. The EPT AI Pod builds AI-native internal apps, MCP connectors, multi-agent workflows, and reusable platform capabilities across Finance, People, and GTM. About the Role As an Enterprise Applied AI Engineer, you will build internal apps for enterprise operations and the shared platform components those apps run on. This includes MCP connectors, multi-agent orchestration, data architecture, evals, monitoring, auditability, and governance. We’re looking for a hands-on engineer who is strong in Python, system design, enterprise integrations, data architecture, and applied AI systems. You should be excited to turn ambiguous business workflows into reliable internal products and shared infrastructure. In this role, you will: • Build internal apps for enterprise operations across Finance, People, and GTM • Build MCP connectors and enterprise integrations with strong auth, permissions, idempotency, retries, and rate-limit handling • Design end-to-end multi-agent workflows with tool routing, human approvals, audit trails, and safe action boundaries • Design data architecture for operational AI systems, including ingestion, schemas, quality checks, lineage, and governance • Build evals, monitoring, metrics, and regression tests for agentic workflows • Create reusable infrastructure, patterns, and components that other enterprise teams can build on • Partner with system owners and business owners to turn messy enterprise workflows into reliable internal products You might thrive in this role if you: • Have strong Python engineering skills for backend services, MCP connectors, agent/tool workflows, eval harnesses, and data ingestion jobs • Have strong system design skills across shared infrastructure, app architecture, reliability, and scaling • Have experience building internal apps, backend services, APIs, workflow systems, or integration platforms • Understand enterprise systems, including controls, approvals, auditability, compliance, and permissions • Have practical AI systems experience with RAG, evals, monitoring, MCP/tool use, structured outputs, or multi-agent workflows • Have strong data architecture fundamentals, including ingestion, modeling, quality, lineage, and governance • Communicate clearly with technical stakeholders, system owners, and business owners • Take high ownership in ambiguous, cross-functional environments About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have

About the Team OpenAI Finance ensures the organization is positioned for long-term success as we pursue our mission. The Strategic Sourcing & Procurement function plays a critical role in enabling OpenAI to deliver impact across research, product development, technology infrastructure, and services by helping the company scale responsibly, securely, and with strong commercial discipline. Our work sits at the intersection of innovation and execution. We partner closely with teams across OpenAI to translate rapidly evolving business needs into scalable, compliant, and economically sound external partnerships. As OpenAI continues to grow at pace, services sourcing is becoming increasingly strategic across the company. Every business unit relies on external service providers in different ways — to extend capacity, access specialized expertise, support operations, and accelerate execution. Done well, Procurement becomes a source of trust and momentum, helping OpenAI move faster with the right partners, stronger commercial outcomes, and the right level of protection. About the Role We are seeking an experienced Strategic Sourcing (GTM) Leader to lead strategic sourcing and commercial enablement for OpenAI’s Go-to-Market organization across B2B and B2C channels. You will manage substantial and rapidly growing spend while shaping sourcing strategies and scalable commercial pathways across Media, Creative, Production, Influencer, Agency, Sponsorships, Analytics, Communications, and Event suppliers in support of high-impact global initiatives. You’ll help evolve our GTM procurement function from reactive deal support into a speed-enabling, scalable commercial engine that delivers cost efficiency, launch readiness, and strong governance in a fast-moving environment. In this role, you will: - Develop and execute sourcing strategies across GTM, Brand, Global Affairs, Events, Growth, and Partnership activities—spanning both B2B and B2C channels—that align with our mission and business objectives. - Lead the strategic sourcing, procurement, and supplier relationship management of key partners across media planning and buying, creative and production, creator/influencer, agencies, communications, sponsorships, partnerships, events, research, and analytics. - Lead and develop a lean, high-performing team of direct reports and contractors while remaining deeply hands-on in complex negotiations and high-volume deal execution; accountable for team output, execution quality, stakeholder experience, and scaling the function effectively. - Negotiate high-value and high-visibility commercial agreements that optimize cost, improve flexibility, and support time-sensitive launches, campaigns, placements, and partnerships. - Partner closely with Marketing , Creative & Production, Growth, Partnerships, Finance, Legal, and other cross-functional stakeholders to understand business priorities and align sourcing strategies accordingly. - Oversee a complex GTM supplier ecosystem, ensuring supplier scalability, rapid onboarding, seamless activation, and timely service delivery across multiple concurrent workstreams. - Identify and implement cost and commercial optimization strategies without compromising quality, speed, business impact, or launch readiness. - Enable major campaigns, brand moments, partnerships, and events by building sourcing approaches that can operate effectively under compressed timelines and evolving business requirements. - Monitor market trends, supplier capabilities, and emerging GTM commercial models to inform sourcing decisions and maintain a competitive advantage. - Provide strategic insights on spend, supplier performance, cycle times, savings, and sourcing initiatives to senior leadership to support fast, informed decision-making. - Ensure compliance with internal policies and external regulations while designing fit-for-purpose procurement pathways that reduce friction and maintain appropriate risk controls. - Build repeatable com

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We are seeking a Mechanical Engineer to lead the engineering, characterization, and productionization of flexible and compliant components in robotic platforms. You will partner closely with cross-functional teams to translate material concepts into engineered subsystems that meet functional, durability, and manufacturing requirements. This role focuses on understanding how soft materials behave in dynamic mechanical systems — including fatigue, creep, hysteresis, wear, and environmental degradation — and designing assemblies that perform consistently at scale. You will work with materials such as elastomers, foams, thermoplastic polyurethanes (TPUs), engineered fabrics, knitted and woven textiles, cables, and other flexible load-bearing or transmission elements, integrating them with rigid hardware, sensors, and actuators using fabrication methods such as bonding, molding, lamination, and sewn assemblies. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will - Design and integrate compliant or flexible materials into mechanical subsystems and rigid hardware interfaces. - Leverage FEA tools to characterize material behavior under operational loads, including tension, compression, abrasion, fatigue, and environmental exposure. - Develop test methods and validation protocols to evaluate durability, performance, and failure modes of soft components. - Collaborate with cross-functional teams to transition early prototypes into manufacturable designs. - Source and evaluate materials in collaboration with supply chain partners and specialty fabricators. - Work with contract manufacturers on fabrication methods such as bonding, lamination, molding, overmolding, cut-and-sew, and composite layups. - Analyze system-level tradeoffs between compliance, durability, manufacturability, and integration constraints. - Document material specifications, test data, and mechanical performance to support design iteration and production readiness. - Investigate field failures and iterate designs based on observed wear patterns and performance degradation. You might thrive in this role if you - Understand mechanical tradeoffs in elastomers, foams, textiles, and flexible composites. - Enjoy working across the full lifecycle from early prototyping through production. - Can develop test fixtures or experiments to characterize material or assembly behavior. - Are comfortable collaborating with both design and manufacturing partners. - Are detail-oriented and rigorous about documentation and repeatability. Preferred qualifications - Degree in mechanical engineering or equivalent. - Experience with A-surface and cosmetic component development - Experience integrating soft or compliant components into robotic, wearable, medical, automotive, or industrial hardware systems. - Familiarity with environmental or durability testing (abrasion, ingress, cyclic loading, UV, temperature). - Experience working with contract manufacturers or specialty fabricators. - Familiarity with material characterization methods for flexible materials. - Experience transitioning flexible-material prototypes into production designs. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, an

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may be strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, topology, firmware, thermals, and failure modes, or design abstractions that make heterogeneous clusters feel like one coherent platform. We do not expect every candidate to have worked at every layer. Some engineers will go deep on systems performance, kernel or runtime behavior, large-scale networking protocols, RDMA, NCCL, GPU hardware behavior, benchmarking, scheduling, or hardware reliability; others will make the platform more usable through APIs, tools, workflows, and developer experience. The common thread is strong engineering judgment and excitement about making enormous compute systems faster, more reliable, and easier to use. This is a general opening for Compute Infrastructure. We will consider candidates for teams across Compute Infrastructure and match you based on your strengths, the problems that motivate you, and where the infrastructure needs are highest. Where you might work - Compute Foundations: Build the low-level platform primitives that make heterogeneous hardware, providers, and data centers repeatable, automatable, and operable at scale. - Fleet / Orchestration: Turn raw capacity into reliable, efficient clusters and scheduling systems that researchers and product teams can use with minimal friction and great experience. - Core Network Engineering: Build and operate the high-performance networking fabrics, protocols, and observability needed for the largest training and serving workloads. - Hardware Health and Observability: Detect, diagnose, remediate, and prevent hardware and fleet-health issues so usable compute stays high across providers and accelerator generations. - Storage: Build scalable, performant, durable storage abstractions that keep data movement and storage access from becoming a bottleneck to research or products. - Agent Infrastructure: Build sandboxed execution infrastructure for agentic workloads across research and production, with strong isolation, reliability, and scale. In this role, you will: - Build and deeply optimize rel

ABOUT THE TEAM We’re hiring software engineers to make OpenAI’s networking teams more productive. These teams build and operate the high-performance networking systems that support OpenAI’s training and inference infrastructure at frontier scale. ABOUT THE ROLE We’re looking for someone who cares deeply about the developer experience of engineers working on complex infrastructure systems — especially around build systems, test architecture, release pipelines, and reliable development workflows. This role will be embedded with OpenAI’s networking team: making it faster, safer, and easier for engineers to build, test, validate, and ship changes across multi-server, networked, and hardware-adjacent environments. In this role you will: - Improve development workflows for engineers building and operating OpenAI’s networking systems - Design and improve continuous deployment, release, and validation pipelines - Build and maintain test harnesses for multi-server, networked, and hardware-backed environments - Improve iteration speed across C++, Python, and build-system-heavy codebases - Partner with engineers to identify friction in CI, testing, debugging, and deployment workflows - Drive testing and reliability strategy for infrastructure components that support large-scale training and inference workloads - Work closely with centralized developer experience teams while staying deeply embedded with the networking engineers closest to the systems You might thrive in this role if: - You are motivated by helping other engineers move faster and with more confidence - You have experience with CI/CD, release pipelines, testing infrastructure, or build systems - You are comfortable moving between C++, Python, and build systems such as CMake, Bazel, or Blaze - You enjoy building test harnesses, automation, and workflow improvements for complex systems - You do not need to be a networking expert, but you are excited to learn enough about the domain to make the team meaningfully more effective - When you see repeated friction — slow builds, flaky tests, brittle release processes, painful debugging, unclear validation — your instinct is to fix the underlying system - You are pragmatic and know how to balance high standards with forward progress - You like going end-to-end: understanding the engineers, the workflows, the codebase, and the operational realities behind the system - You are self-directed and comfortable operating with ambiguity in a high-context infrastructure environment About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with th

About the Team Our Cyber team builds AI systems and products that help trusted defenders understand and respond to cyber threats while improving the safety and reliability of frontier models in security-sensitive settings. The team works across product engineering, model training, evaluations, safeguards, and deployment to make advanced cyber capabilities useful to defenders and responsibly managed. We collaborate closely with Safety/Preparedness, Research, Security, Legal, Communications, GTM, and external partners across OpenAI’s broader cyber work. About the Role We’re looking for research and software engineers to join Codex Cyber. You’ll help define and ship security products, work with trusted defenders and customers, shape model training and access patterns, and build research and evaluation systems for assessing cyber capabilities, validating safeguards, and improving training data. This role is hands-on and cross-functional, connecting product launches, model development, safety work, and real-world security use cases. In this role, you will: - Help define and execute the technical roadmap for Codex Cyber’s security products, including evaluations, safeguards, trusted-defender workflows, and deployment decisions. - Work with trusted defenders, customers, and partner teams to understand cyber use cases, evaluate risk, and turn feedback into product and research priorities. - Shape cyber-specific model training and access patterns, including data, evaluations, validation, and deployment criteria. - Build and validate systems for measuring cyber capabilities, monitoring misuse risk, and proving safeguards work in practice. - Collaborate with Safety/Preparedness, Research, Security, Legal, Communications, Go-to-Market, and external partners on company-wide cyber priorities. - Translate frontier cyber research into launch-ready tools, operational playbooks, and durable infrastructure for Codex and security products. You might thrive in this role if you: - Enjoy 0 -> 1 environments, can navigate ambiguity, are excited to build security products that bring frontier AI capabilities to trusted defenders responsibly. - Can move fluidly between product launches, customer and defender partnerships, model training, evaluation science, and security research. - Have strong programming skills in Python, TypeScript/JavaScript, or similar languages, with the judgment to build reliable systems in ambiguous, high-stakes domains. - Think clearly about cyber capability, misuse risk, access patterns, safeguards, and deployment tradeoffs in high-stakes environments. - Have experience in ML systems, security products, cyber evaluations, model training, safety engineering, or trusted customer deployments. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance f

About the Team The Strategic Initiatives & Operations team is in need of a Technical Program Manager (TPM) to streamline our processes, including full safety governance and integration of various safety research and mitigations into our ChatGPT, API, and any frontier models. This role is critical for driving safe deployment of our new models, synthesizing inputs from multiple stakeholders, ranging across research, product, engineering, legal and policy, and ensuring all the risks are effectively and properly monitored, mitigated or resolved. About the Role As a TPM, you will be responsible for critical tasks ranging from tracking safety research progress and risk tables to overseeing the quality of human data campaigns – acting as the connective tissue to enhance the deployment of OpenAI’s safety system. Additionally, you will create and execute a compute roadmap for your team to ensure that our top priorities are resourced while taking advantage of new opportunities to make key safety research discoveries. Your primary focus will be to ensure our models are qualified for safe deployment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Manage key risk areas and corresponding stakeholders. - Keep track of a stack of existing and future mitigations for every major product and model deployment. - Standardize the lifecycle of risk assessment, setting safety bars, consolidating inputs from multiple stakeholders across research, product, engineering, legal and policy, pre-launch safety reviews and post-launch followup. - Manage pre-launch safety reviews. - Share launch calendars and key safety practices and evaluations with our key parter (i.e. Microsoft). - Develop comprehensive documentation for all the safety work, including metrics, evaluations, and progress tracking across multiple teams within OpenAI. - Help with publishing and open sourcing safety learnings, standards, datasets and benchmarks with the public. You might thrive in this role if you: - Possess an advanced degree in a hard science, with a PhD being advantageous, or a demonstrated track record of engineering expertise. - Have an extensive track record of successfully delivering high-profile, complex technical projects against tight deadlines. - Are technically adept, and have effectively partnered with engineering and fundamental research teams of the highest caliber. - Expertise in designing and implementing simple, scalable processes that solve complex problems. - Are relentlessly resourceful and thrive in ambiguous, fast-paced environments. - Strong knowledge of content integrity and moderation, including industry best practices and regulatory guidelines. - Exceptional written and verbal communication skills. - Care about AGI safety. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered f

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) which benefits all of humanity. This long-term undertaking brings the world’s best scientists, engineers, and business professionals into one lab together to accomplish this. In pursuit of this mission, our Go To Market (GTM) team is responsible for helping customers learn how to leverage and deploy our highly capable AI products across their business. The team is made of Sales, Solutions, Support, Marketing, and Partnership professionals that work together to create valuable solutions that will help bring AI to as many users as possible. About the Role Our GTM team is uniquely positioned to help customers realize the transformative potential of advanced AI models for their businesses and end users. As an individual contributor on the GTM Operations team, you’ll play a critical role in designing and scaling the operational systems that power our sales organization. This role will serve as a trusted partner to GTM leadership, building the end-to-end ops design for sales lifecycle from lead routing through territory design, opportunity management, deal execution, and delivery readiness. This role combines systems and process design with operational performance management, delivering insights and driving automation to improve field efficiency and velocity. You’ll collaborate cross-functionally with Marketing Ops, Enterprise Systems, Product, Delivery, Finance, Enablement, Legal, Deal Desk, and Security to develop scalable infrastructure, streamline workflows, and enable scalable growth across the business. In this role, you will: GTM Data,Governance & Routing: Create a reliable GTM data foundation that makes SFDC easier to use and ensures leads, accounts, and opportunities are accurately routed, defined, enriched, and actionable. - Design and manage lead and campaign routing; define requirements and partner with systems and marketing ops on build. - Implement alerting, monitoring, and reporting to ensure routing accuracy and responses. - Drive data quality and enrichment strategy across core GTM objects. - Establish cross-object definitions, ownership, source-of-truth standards, and governance for SFDC fields, layouts, process changes, and field feedback on data and routing issues. TAM, Accounts & Territories: Create a clean, scalable account and territory foundation that aligns coverage with market opportunity and enables efficient selling. - Own account structure (parent/child), TAM integrity, and Salesforce account data health. - Drive territory design process and execution as part of fiscal planning cycles. - Manage account ownership, book movements, and territory adjustments. - Define account hierarchy, account team structures, and rules of engagement across segments, overlays, and global coverage. Sales Process & Opportunity Management: Drive consistent, high-quality pipeline execution through standardized processes, automation, and governance. - Own opportunity design (stages, required fields, inspection criteria). - Enforce pipeline governance (accuracy, staleness, coverage, generation health). - Build workflows and automations (e.g., AI-assisted field population) to increase rep productivity. - Monitor and drive adherence to process; partner with enablement on rollout and adoption. - Capture and operationalize competitive intelligence within systems. - Own operating cadences for work intake, prioritization, systems planning, process health, change management, and delivery of systems improvements (“sales paper cuts”). Revenue & Consumption Operations: Design and scale the operational systems that move priority revenue motions from commercial commitment through delivery and customer value. - Design and test processes, systems, and seller workflows for consumption-based motions, including opportunity-to-delivery handoffs and readiness requirements. - Define the SFDC objects, stage requirements, rep surfaces, and visibility needed to suppo

About the Team The team’s mission is to accelerate the secure evolution of agentic AI systems at OpenAI. To achieve this, the team designs, implements, and continuously refines security policies, frameworks, and controls that defend OpenAI’s most critical assets—including the user and customer data embedded within them—against the unique risks introduced by agentic AI. About the Role As a Security Engineer on the Agent Security Team, you will be at the forefront of securing OpenAI’s cutting-edge agentic AI systems. Your role will involve designing and implementing robust security frameworks, policies, and controls to safeguard OpenAI’s critical assets and ensure the safe deployment of agentic systems. You will develop comprehensive threat models, partner tightly with our Agent Infrastructure group to fortify the platforms that power OpenAI’s most advanced agentic systems, and lead efforts to enhance safety monitoring pipelines at scale. We are looking for a versatile engineer who thrives in ambiguity and can make meaningful contributions from day one. You should be prepared to ship solutions quickly while maintaining a high standard of quality and security. We’re looking for people who can drive innovative solutions that will set the industry standard for agent security. You will need to bring your expertise in securing complex systems and designing robust isolation strategies for emerging AI technologies, all while being mindful of usability. You will communicate effectively across various teams and functions, ensuring your solutions are scalable and robust while working collaboratively in an innovative environment. In this fast-paced setting, you will have the opportunity to solve complex security challenges, influence OpenAI’s security strategy, and play a pivotal role in advancing the safe and responsible deployment of agentic AI systems. You’ll be responsible for: - Architecting security controls for agentic AI – design, implement, and iterate on identity, network, and runtime-level defenses (e.g., sandboxing, policy enforcement) that integrate directly with the Agent Infrastructure stack. - Building production-grade security tooling – ship code that hardens safety monitoring pipelines across agent executions at scale. - Collaborating cross-functionally – work daily with Agent Infrastructure, product, research, safety, and security teams to balance security, performance, and usability. - Influencing strategy & standards – shape the long-term Agent Security roadmap, publish best practices internally and externally, and help define industry standards for securing autonomous AI. We’re looking for someone with: - Strong software-engineering skills in Python or at least one systems language (Go, Rust, C/C++), plus a track record of shipping and operating secure, high-reliability services. - Deep expertise in modern isolation techniques – experience with container security, kernel-level hardening, and other isolation methods. - Hands-on network security experience – implementing identity-based controls, policy enforcement, and secure large-scale telemetry pipelines. - Clear, concise communication that bridges engineering, research, and leadership audiences; comfort influencing roadmaps and driving consensus. - Bias for action & ownership – you thrive in ambiguity, move quickly without sacrificing rigor, and elevate the security bar company-wide from day one. - Cloud security depth on at least one major provider (Azure, AWS, GCP), including identity federation, workload IAM, and infrastructure-as-code best practices. - Familiarity with AI/ML security challenges – experience addressing risks associated with advanced AI systems (nice-to-have but valuable). About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: 1. Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. 2. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. 3. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework https://openai.com/index/updating-our-preparedness-framework/, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE As AI agents become more capable at software engineering, and automate more of our internal work, they could become a dangerous cyber threat. People in this role will help OpenAI prepare for security threats from advanced AI agent insiders. IN THIS ROLE, YOU WILL: - Identify paths by which capable future internal AI agents could compromise OpenAI. - Design security controls - focusing on measures with long lead times that benefit from advanced preparation. - Stress-test defenses with AI agent evaluations and penetration tests YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Are deeply technical across security and modern infrastructure, and are comfortable digging into the details of operating systems, cloud, containers, CI/CD, or distributed systems. - Have strong software engineering skills and enjoy building prototypes yourself. - Are interested in engaging with stakeholders and can do so effectively. - Bonus: have experience securing cloud infrastructure, and are deeply familiar with core components of the AI stack. Compensation Range: $293K - $405K USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-complia

ABOUT THE TEAM The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that lets other builders move faster without taking on hidden reliability risk. ABOUT THE ROLE As an Infrastructure Engineer on the Statsig team, you will build and scale the foundational systems behind OpenAI's experimentation and rollout platform. You will work on the distributed control plane, SDK and server evaluation paths, ingestion pipelines, analytics foundations, and operational tooling that make launches safe and measurable at OpenAI scale. This role is deeply technical and centered on performance, scalability, reliability, and correctness. You will design systems that serve low-latency configuration decisions, handle high-throughput event ingestion, preserve data availability for experimentation and analytics workflows, and keep critical launch infrastructure dependable as usage grows. The work matters because OpenAI's next phase depends on learning quickly without compromising safety or reliability. Every major product surface needs a trusted way to evaluate changes, progressively roll them out, understand impact, and recover cleanly. Statsig is one of the core infrastructure layers that makes that possible. IN THIS ROLE, YOU WILL - Design and operate low-latency configuration delivery systems powering feature flags, dynamic configs, and progressive rollouts across OpenAI product suites. - Scale SDK, server-side evaluation, and control-plane systems so high-volume services can depend on Statsig without adding user-visible latency or operational fragility. - Build high-throughput data ingestion and analytics infrastructure for experimentation, product analytics, feature performance monitoring, and model or product measurement workflows. - Improve performance, efficiency, reliability, and observability of core Statsig infrastructure as OpenAI products scale globally. - Optimize query performance, data freshness, and data availability for teams making launch decisions from experimentation and analytics workflows. - Strengthen operational excellence through bett

About the Team The Sora team is working on making video a key capability of OpenAI’s foundation models. We are a hybrid research and product team that seeks to understand and expand the capabilities of our video models, while ensuring their reliability and safety. We accomplish this both through directly studying and experimenting with the models, as well as deploying them into the real-world to distribute their benefits widely. About the Role As a Distributed Systems/ML engineer, you will work on improving the training throughput for our internal training framework and enable researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Collaborate with researchers to enable them to develop systems-efficient video models and architectures - Apply the latest techniques to our internal training framework to achieve impressive hardware efficiency for our training runs - Profile and optimize our training framework You might thrive in this role if you: - Have experience working with multi-modal ML pipelines - Love diving deep into systems implementations and understanding their fundamentals in order to improve their performance and maintainability - Have strong software engineering skills and are proficient in Python. - Have experience understanding and optimizing training kernels - Are passionate about understanding stable training dynamics About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, pl

About the Team The ChatGPT organization at OpenAI supports our mission by bringing advanced AI capabilities to hundreds of millions of users worldwide. The Image Generation team is responsible for one of the fastest-growing experiences in ChatGPT, enabling users to create, edit, and transform images through natural language. Recent breakthroughs in multimodal AI have dramatically improved image quality, instruction following, editing precision, consistency, and text rendering. We're building the systems and experiences that turn these research advances into products used daily by creators, professionals, businesses, and consumers around the world. Our team sits at the intersection of research, product, design, and infrastructure. We work closely with model researchers, mobile engineers, frontend engineers, and platform teams to build intuitive experiences and scalable systems that power image generation at global scale. Whether users are creating marketing assets, visualizing ideas, editing photos, designing products, or simply exploring their creativity, our goal is to make visual creation feel as natural as having a conversation. About the Role We are looking for an experienced Full Stack Engineer to join the Image Generation team and help shape the future of AI-powered visual creation. In this role, you'll own features end-to-end across both frontend and backend systems, building the experiences that enable users to generate, edit, organize, and interact with images inside ChatGPT. You'll work across the entire stack—from highly interactive user interfaces and real-time workflows to backend services, APIs, orchestration systems, and data infrastructure. This role is ideal for engineers who enjoy moving fluidly between product development and systems engineering, collaborating closely with design, product, and research teams to rapidly bring new AI capabilities to users. You'll help define entirely new interaction paradigms as multimodal AI continues to evolve. In this role, you will: - Design, build, and launch end-to-end product experiences for image generation and image editing within ChatGPT. - Develop highly interactive frontend experiences that make sophisticated AI capabilities feel intuitive, fast, and delightful. - Build scalable backend services, APIs, and workflows that power image creation, editing, storage, sharing, and retrieval. - Partner closely with researchers to rapidly prototype and productionize new multimodal capabilities. - Collaborate with Product, Design, Data Science, and Engineering teams to identify high-impact opportunities and execute against them. - Own projects from concept through launch, including technical design, implementation, experimentation, measurement, and iteration. - Optimize performance across the stack, from frontend responsiveness and rendering to backend latency, reliability, and scalability. - Design systems that can support millions of users generating and interacting with visual content simultaneously. - Leverage experimentation and user insights to improve engagement, usability, quality, and product outcomes. - Contribute to engineering best practices around architecture, testing, observability, developer productivity, and operational excellence. - Help define the future roadmap for AI-powered creative tools and visual experiences. You might thrive in this role if you: - Have experience building and shipping production-grade applications across both frontend and backend systems. - Are comfortable working with modern web technologies such as React, TypeScript, and contemporary frontend frameworks. - Have experience building scalable backend services, APIs, and distributed systems. - Enjoy owning products end-to-end and can seamlessly move between user experience challenges and infrastructure decisions. - Have strong product instincts and enjoy thinking deeply about how users interact with technology. - Are highly analytical and comfortable using experimentation, metrics, and

About the Team The GTM (Go-To-Market) Innovation team is an internal powerhouse revolutionizing how we engage customers through groundbreaking applications of our technology. As an incubator, we amplify the impact of Sales, Technical Success, Enablement, and Revenue Operations by deploying our technology at scale. This team applies advanced capabilities to real-world interactions — reshaping conversations with customers, learning from every exchange, and finding novel ways to show the value of our technology. About the Role We’re looking for backend software engineers with a product mindset to join the GTM Innovation team. You’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: - Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts - Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain - Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them - Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems - Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: - Have 4+ years of experience as a software/ML/product engineer working on user-facing systems - Former founder, or early engineer at a startup who built a product from scratch is a plus - Are fluent in Python or JavaScript and comfortable building full-stack applications - Have built or prototyped LLM-powered workflows using the OpenAI API (or similar) - Take initiative, move quickly, and operate with a strong sense of ownership - Enjoy working closely with end users and shaping 0→1 products - Are collaborative, curious, and motivated to make an outsized impact at the frontier of AI About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) u

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Mechanical Engineer, you will help design, validate, and scale the cooling and mechanical systems that make high-density AI compute possible. You will work across thermal architecture, equipment development, manufacturing validation, construction, commissioning, deployment, and operations, partnering with research, hardware engineering, data center engineering, supply chain, EHS, operations, and external delivery partners. About The Role We are seeking a senior mechanical infrastructure engineer to lead the development of reliable, efficient, safe, and scalable thermal architectures for high-density, liquid-cooled AI data centers. This role is ideal for someone who can translate evolving compute and rack-level thermal requirements into practical infrastructure designs, evaluate complex equipment and vendor solutions, and drive technical decisions across facilities, hardware, controls, telemetry, testing, commissioning, and operations. The ideal candidate has deep hands-on experience with mission-critical mechanical systems at data center or comparable critical infrastructure scale, including chilled water plants, condenser water systems, cooling towers, dry coolers, pumps, heat exchangers, CDUs, manifolds, CRAHs, air handlers, filtration, water treatment, controls, liquid distribution, and high-density rack cooling interfaces. Key Responsibilities - Define mechanical and cooling infrastructure requirements and reference architectures for AI data center campuses, including heat rejection, chilled water, condenser water, liquid cooling distribution, air handling, containment, filtration, water treatment, controls, and metering. - Review and develop basis-of-design documents, design narratives, P&IDs, mechanical schedules, equipment specifications, thermal capacity models, hydraulic models, CFD analysis, controls sequences, and commissioning requirements. - Evaluate mechanical architectures for high-density compute, including direct-to-chip liquid cooling, CDU topology, facility water interfaces, manifolds, quick disconnects, hoses, heat exchangers, pumping strategies, leak detection, serviceability, and failure isolation. - Partner with electrical, controls, hardware, networking, construction, and operations teams to ensure cooling systems support liquid-cooled GPU rack deployments and reliable facility operation. - Develop technical specifications and acceptance criteria for chillers, cooling towers, dry coolers, evaporative coolers, pumps, heat exchangers, CDUs, manifolds, valves, filters, water treatment systems, CRAHs, air handlers, VFDs, controls panels, sensors, and monitoring devices. - Lead technical evaluation of equipment vendors, manufacturers, design consultants, commissioning agents, contractors, and testing laboratories; review submittals, P&IDs, control diagrams, performance curves, test reports, certifications, and quality documentation. - Drive factory acceptance testing, site acceptance testing, witness testing, pressure testing, leak testing, thermal performance testing, reliability testing, interoperability testing, and integrated systems testing for critical equipment and high-density rack deployments. - Help design and operate a hardware and data center infrastructure R&D laboratory used to validate new cooling equipment, liquid-cooled GPU rack designs, operating envelopes, fault scenarios, telemetry, and facility-hardware interactions. - Collaborate with hardware manufacturers to evaluate L10 and L11 test procedures, yield, throughput, reliability, serviceability, and readiness for large-scale deployment. - Define telemetry and controls requirements for mec

About the Team The Preparedness team is an important part of the Safety Systems https://openai.com/safety/safety-systems org at OpenAI, and is guided by OpenAI’s Preparedness Framework https://openai.com/index/updating-our-preparedness-framework/. Frontier AI models have the potential to benefit all of humanity, but also pose increasingly severe risks. To ensure that AI promotes positive change, the Preparedness team helps us prepare for the development of increasingly capable frontier AI models. This team is tasked with identifying, tracking, and preparing for catastrophic risks related to frontier AI models. The mission of the Preparedness team is to: 1. Closely monitor and predict the evolving capabilities of frontier AI systems, with an eye towards misuse risks whose impact could be catastrophic to our society 2. Ensure we have concrete procedures, infrastructure and partnerships to mitigate these risks and to safely handle the development of powerful AI systems Preparedness tightly connects capability assessment, evaluations, and internal red teaming, and mitigations for frontier models, as well as overall coordination on AGI preparedness. This is fast paced, exciting work that has far reaching importance for the company and for society. About the Role We’re hiring a Data Scientist to help build, evaluate, and continuously improve mitigations that prevent extreme harms from AI systems. This role is for an experienced, highly autonomous individual contributor who can take ambiguous problem statements, structure rigorous analyses, and translate findings into actionable product and policy changes. This position goes beyond “running evals.” You’ll help create mitigation intelligence and monitoring systems that enable OpenAI to detect issues early, measure effectiveness over time, and reduce both over-blocking (unnecessary friction) and under-blocking (missed harm). WHAT YOU’LL DO - Evaluate and improve mitigation systems, including classifiers and detection pipelines across domains (e.g., biosecurity, cybersecurity, and emerging risk areas). - Diagnose false positives and false negatives with deep error analysis, root cause investigation, and clear recommendations for mitigation adjustments. - Build monitoring and measurement frameworks to track mitigation effectiveness over time and across user segments and use cases. - Identify trends in over-blocking vs. under-blocking, quantify customer impact, and propose prioritized interventions. - Develop insights from customer feedback, complaints, and usage patterns to detect shifts in adversarial behavior and system failure modes. - Expand risk monitoring into new areas, including cybersecurity threats and model loss-of-control or sabotage scenarios, in partnership with domain experts. - Communicate results to technical and executive stakeholders with crisp narratives, decision-ready metrics, and clear tradeoffs. You might thrive in this role if you are: - An autonomous operator: you can take a problem statement and independently structure the analysis end-to-end. - Strong at executive-ready communication: concise, clear, and outcome-oriented. - Skilled in turning analysis into productable changes: you’re comfortable influencing across functions to drive mitigation improvements. QUALIFICATIONS - Significant experience in data science or applied analytics in high-stakes domains (e.g., security, trust & safety, abuse prevention, fraud, platform integrity, or reliability). - Strong foundations in experimentation, causal thinking, and/or observational inference; ability to design robust measurement under imperfect data. - Fluency in SQL and Python (or equivalent) for analysis, modeling, and building monitoring workflows. - Experience building metrics, dashboards, and operational monitoring that meaningfully changes outcomes (not just reporting). - Track record of driving cross-functional impact with engineering, product, and research partners. - Cybersecurity data science experience (s

About the Team OpenAI’s Stargate Infrastructure team is building and operating the systems that power next-generation AI workloads at massive scale. This includes deploying and managing clusters, networks, and data center infrastructure across first-party and partner environments. As the scale and complexity of these systems grow, we are investing in agentic systems and intelligent automation to improve how infrastructure is deployed, operated, and debugged. This team focuses on applying AI-driven approaches to real-world infrastructure workflows—enabling faster execution, higher reliability, and scalable operations. About the Role We are seeking an IC Agentic Engineering Manager to lead the development and application of agent-based systems for infrastructure delivery and operations within Stargate. This is a player-coach role: you will contribute directly to system design and implementation while leading a small team. You will focus on applying agentic systems to infrastructure workflows such as deployment orchestration, system bring-up, issue triage, debugging, and capacity management. This role is not focused on building general-purpose agent platforms. Instead, it is centered on applying agentic systems to solve concrete infrastructure problems, working closely with hardware, networking, and cluster teams. Key Responsibilities - Design and build agent-based systems to support infrastructure deployment and operations - Identify high-impact opportunities to apply agents across workflows such as: - cluster bring-up and deployment readiness - incident triage and root cause analysis - system validation and health monitoring - capacity management and operational decision-making - Lead a small team while contributing directly as an IC across system design, development, and integration - Partner with infrastructure, hardware, and networking teams to integrate agentic systems into production workflows - Develop systems that leverage telemetry, logs, and system signals to enable closed-loop automation - Define evaluation frameworks to measure system effectiveness, reliability, and operational impact - Drive iteration from prototype to production, ensuring robustness and scalability Qualifications - Strong software engineering background in distributed systems, infrastructure, or platform engineering - Experience building production automation systems or data-driven operational tooling - Experience applying AI, ML, or agent-based approaches to real-world systems or workflows - Ability to operate as a hands-on IC while leading a small team - Experience working cross-functionally with infrastructure, hardware, or systems teams - Strong problem-solving skills in complex, ambiguous environments Preferred Skills - Experience with LLM-based systems, agents, or autonomous workflows - Background in infrastructure operations, SRE, or large-scale system deployment - Experience working on cluster bring-up, debugging, or data center infrastructure systems - Familiarity with telemetry, monitoring systems, and observability pipelines - Experience building internal tools or platforms for engineering productivity and operations About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmat

ABOUT THE TEAM The Human Data team at OpenAI is responsible for identifying and mitigating risks in advanced AI systems by designing evaluations, surfacing vulnerabilities, and collaborating closely with researchers to strengthen model reliability and public trust. ABOUT THE ROLE As a Technical Program Manager, you will lead initiatives that test the safety and robustness of OpenAI’s models through creative experimentation and structured evaluation. You’ll coordinate efforts across research and engineering teams to transform ambiguous risks into concrete research programs and influence future model development and deployment. We’re looking for people who are technically savvy, comfortable with ambiguity, and excited about shaping the future of safe AI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Lead programs that explore unexpected model behaviors and identify failure modes. - Translate vague or emergent risk signals into clear priorities and actionable research plans. - Design and run creative evaluations, experiments, and red-teaming campaigns. - Collaborate with research, product, and deployment teams to integrate findings into model training and deployment cycles. - Develop repeatable systems for tracking model performance and understanding emerging behavior patterns. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong experience in technical program management, with excellent organizational and communication skills. - Are familiar with large language models, prompt engineering, or model evaluation techniques. - Are comfortable managing fast-paced, high-uncertainty projects and shaping them from the ground up. - Are creative and resourceful in devising new methods for testing model behavior and performance. - Can effectively coordinate across technical and non-technical stakeholders to drive alignment and execution. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security ob

ABOUT THE TEAM OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. ABOUT THE ROLE On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. IN THIS ROLE, YOU WILL: - Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. - Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. - Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. - Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. - Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. - Contribute to runtime improvements, compute/communication overlapping, and scaling efforts for frontier AI workloads. YOU MIGHT THRIVE IN THIS ROLE IF YOU HAVE: - 3+ years of experience working on AI infrastructure, including kernels, systems, or hardware-software co-design - Hands-on experience with accelerator platforms for AI at data center scale (e.g., TPUs, custom silicon, exploratory architectures). - Strong understanding of kernels, sharding, runtime systems, or distributed scaling techniques. - Familiarity with optimizing LLMs, CNNs, or recommender models for hardware efficiency. - Experience with performance modeling, system debugging, and software stack adaptation for novel architectures. - Exposure to mobile accelerators is welcome, but experience enabling data center-scale AI hardware is preferred. - Ability to operate across multiple levels of the stack, rapidly prototype solutions, and navigate ambiguity in early hardware bring-up phases - Interest in shaping the future of AI compute through exploration of alternatives to mainstream accelerators. To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional in

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing multimodal data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We’re looking to advance how OpenAI prepares, curates, synthesizes and understands multimodal data at scale. You’ll work on research and production problems like synthesizing multimodal content (images, audio, and video) and their supervisions, improving noisy data pipelines, building better quality filters, using models to automate data prep, and measuring whether changes in the dataset improve model performance. We Expect You To - Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. - Own and drive a research agenda, from choosing the right multimodal data problems to carrying long-running work through to impact. - Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have - Experience with multimodal learning, audio, vision, video, synthetic data, or data-centric ML. - Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. - Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pd

About the Team We bring OpenAI's technology to the world through products like ChatGPT and the OpenAI API. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role We are looking for an experienced Research Engineer to work on retrieval & search problems across our API and ChatGPT. As the AI landscape has evolved over the last few years, retrieval & search have emerged as key use cases for our models, and we are investing in ensuring that we can offer these search-based product experiences for our users. You will be at the center of our retrieval & search efforts as a company, and the progress you drive here will reach millions of end users. In this role, you will: - Work on retrieval & search algorithms and methodologies in close collaboration with our research team, including problems in such domains as document search, enterprise search, knowledge retrieval, and web-scale search. - Deploy these search methodologies into production in both the API and ChatGPT to be used by millions of end users. - Explore novel research topics in retrieval & search that may inform our product strategy in the medium and long term. - Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world You might thrive in this role if you: - Have extensive prior experience building and maintaining production machine learning systems. - Have prior experience working with vector databases, search indices, or other data stores for search and retrieval use cases - Have prior experience building and iterating on internet-scale search systems - Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done - Have the ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines . About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and re

About the Team: OpenAI's mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. Our API is the industry's most widely adopted AI platform, empowering startups, indie developers, and Fortune 500 companies alike. Through multimodal APIs—spanning real-time interactions, text-to-speech (TTS), speech generation, and image generation—we enable users to harness the full potential of diverse AI modalities effectively and at scale. About the Role: We are seeking an Engineering Manager to lead our multimodal API product suite. Your team will be responsible for delivering innovative APIs across real-time processing, speech transcription, speech generation, and image creation. You will own the product roadmap for how we evolve our multimodal API offerings, and you will build the products that allow developers to reach millions of end users through AI audio, video, and images. In this role, you will: - Build, mentor, and grow a high-performing engineering team focused on multimodal API products – including our realtime API, our transcription models (Whisper), our speech generation models (TTS), and our image generation APIs (DALLE and native 4o). - Collaborate closely with product managers, designers, and other stakeholders to define the strategic vision and product roadmap. - Work closely with our research teams to improve our core multimodal models for API customer use cases. - Guide technical and architectural decisions, emphasizing scalability, robustness, and user experience. - Foster a culture of innovation, continuous improvement, and accountability within your team. Qualifications: - Proven experience managing engineering teams that deliver complex, high-quality products at scale. - Strong technical background and proficiency in modern software engineering practices and system architecture. - Excellent collaboration and communication skills to effectively coordinate across diverse teams and stakeholders. - Familiarity with or strong interest in multimodal AI, including speech technologies, real-time systems, and image generation. - Ability to operate effectively in a fast-paced, ambiguous startup environment. Preferred Qualifications: - Experience developing multimodal systems or APIs in AI/ML domains, especially around image generation, audio generation, or speech transcription. - Familiarity with real-time streaming technologies, audio processing, and computer vision. - Hands-on experience with cloud platforms and distributed architectures. Location: This role is in-person at our San Francisco office. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal h

ABOUT THE TEAM The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. ABOUT THE ROLE We believe that the final enabler for AGI is spending compute on context. As a Context Researcher on Agent Post-Training, you will scale compute spent on context. You will get to work in our frontier training stack on enabling the next paradigm of model training with a clear product interface for iterative deployment (Codex Chronicle). You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. IN THIS ROLE, YOU MIGHT - Design and run experiments that improve scaling of compute on context. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with. - Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next. - Are comfortable working across research, product, infrastructure, data

ABOUT THE TEAM The Intelligence and Investigations team seeks to rapidly identify and mitigate abuse and strategic risks to ensure a safe online ecosystem. We are dedicated to identifying emerging abuse trends, analyzing risks, and working with our internal and external partners to implement effective mitigation strategies to protect against misuse. Our efforts contribute to OpenAI's overarching goal of developing AI that benefits humanity. The Strategic Intelligence & Analysis (SIA) team provides safety intelligence for OpenAI’s products by monitoring, analyzing, and forecasting real-world abuse, geopolitical risks, and strategic threats. Our work informs safety mitigations, product decisions, and partnerships, ensuring OpenAI’s tools are deployed securely and responsibly across critical sectors. ABOUT THE ROLE As an Agentic Risk Analyst, you will shape OpenAI’s operating picture for current agentic risk across products and platforms. You will bring a strategic, system-level perspective to current risks, connecting individual incidents, technical findings, abuse patterns, and external developments to relevant workstreams, mitigations, owners, dependencies, and residual gaps. You will analyze how risks emerge through autonomy, multi-step task execution, tool use, memory, retrieval, connectors, computer-use capabilities, and multi-agent workflows, with a particular focus on both adversarial misuse and unintended system behavior. By synthesizing signals from investigations, evaluations, red teaming, security reviews, product launches, external research, and real-world incidents, you will maintain a current view of material risks and evolving threat patterns. Your work will help turn complex and often ambiguous signals into coordinated decisions and measurable follow-through across product, safety, security, policy, and governance teams. You will work closely with investigators, engineers, product, policy, safety, and security teams, and measurement and forecasting experts who lead longer-horizon risk discovery and scenario work to maintain a shared operating picture of current risks, mitigation priorities, owners, and dependencies. This is an opportunity to help shape how OpenAI coordinates decisions and follow-through across the evolving risk landscape of increasingly capable agentic systems, ensuring that safety decisions keep pace with rapidly advancing technology. IN THIS ROLE, YOU WILL: - Build and maintain a current, company-wide portfolio of material agentic risks across OpenAI’s products, platforms, and emerging capabilities, mapping each risk to relevant workstreams, owners, mitigations, dependencies, decisions, and residual gaps. - Run a cross-functional intake and review cadence for signals from across OpenAI and the broader ecosystem to identify emerging risks, evolving threat patterns, and important shifts in the agentic risk landscape, routing findings to the right owners and decision-makers - Connect individual incidents, technical findings, evaluations, and weak signals to broader system-level trends, producing clear assessments of impact, severity, evidence, uncertainty, priority, and recommended action. - Assess how emerging capabilities, product changes, ecosystem developments, and adversary adaptation may affect current risk priorities and launch readiness, surfacing risks that are unowned, stalled, or under-mitigated for decision and escalation, and tracking residual risk after launch. - In partnership with colleagues who lead horizon scanning, use relevant external developments across AI safety and security research, public incidents, adversarial activity, industry standards, emerging technologies, and competitor products, as inputs to current risk prioritization and mitigation decisions at OpenAI. - Apply and refine practical frameworks and taxonomies for current agentic failure modes, control gaps, abuse patterns, and potential downstream harms across products, deployment environments, and user workflows,

About the Team The Safety Systems team is dedicated to ensuring the safety, robustness, and reliability of AI models and their deployment in the real world. Learn more about OpenAI’s approach to safety. https://openai.com/safety/ Building on the many years of our practical alignment work and applied safety efforts, Safety Systems addresses emerging safety issues and develops new fundamental solutions to enable the safe deployment of our most advanced models and future AGI, to make AI that is beneficial and trustworthy. About the Role At OpenAI, we're dedicated to advancing artificial intelligence, and we know that creating a secure and reliable platform is vital to our mission. That's why we're seeking a software engineer to help us build out our trust and safety capabilities. In this role, you'll work with our entire engineering team to design and implement systems that detect and prevent abuse, promote user safety, and reduce risk across our platform. You'll be at the forefront of our efforts to ensure that the immense potential of AI is harnessed in a responsible and sustainable manner. Your Responsibilities: - Architect, build, and maintain anti-abuse and content moderation infrastructure designed to protect us and end users from unwanted behavior. - Work closely with our other engineers and researchers to utilize both industry standard and novel AI techniques to measure, monitor and improve AI models’ alignment to human values. . - Diagnose and remediate active incidents on the platform and build new tooling and infrastructure that address the root causes of system failure. You might thrive in this role if: - You have built and run production services in a high growth, rapidly scaling environment. - You can debug live issues and restore systems quickly. - You have worked on content safety, fraud, or abuse, or are motivated and excited to work on present-day (“now-term”) AI safety. - You have experience with Python or with modern languages such as C++, Rust, or Go, and are able to quickly ramp up on Python. - You understand the trade-offs of capabilities and risks and navigate them to deploy novel products and features safely. - You can critically assess risks of a new product or feature and devise innovative solutions to mitigate these risks without harming the product experience. - You’re pragmatic. You know when to build a quick, good-enough fix, and when to invest in a robust, lasting solution. - You possess strong project management skills. You are self-directed and can remove roadblocks to drive projects to completion with minimal guidance. - You’ve deployed classifiers or machine learning models, or are excited to learn about modern ML infra. Our tech stack - Our infrastructure is built on Terraform, Kubernetes, Azure, Python, Postgres, and Kafka. - While we value experience with these technologies, we are primarily looking for engineers with strong technical skills who understand the fundamental problems these tools solve, and can quickly pick up new tools and frameworks. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Backgr

ABOUT THE TEAM The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. ABOUT THE ROLE We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. IN THIS ROLE, YOU WILL: - Design, build, and operate networking systems that support large-scale AI training and inference infrastructure - Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems - Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure - Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation - Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-performance GPU interconnects - Define and operationalize networking protocols, readiness criteria, and continuous validation systems - Partner closely with compute, storage, hardware, and infrastructure teams to ensure networking scales predictably with fleet growth - Contribute to architecture decisions around topology design, capacity planning, failure domains, and network reliability - Diagnose complex distributed systems and networking issues across large heterogeneous compute environments YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have experience building or operating large-scale networking or distributed systems infrastructure - Are comfortable working close to the hardware/software boundary - Have experience with Linux networking, kernel systems, NICs, RDMA, or performance-sensitive infrastructure software - Have worked with high-performance networking technologies such as InfiniBand, RoCE, DPDK, or large-scale Ethernet fabrics - Have experience with datacenter networking, WAN systems, or host networking stacks - Enjoy debugging complex systems and performance bottlenecks across multiple layers of the stack - Are comfortable writing production software in languages such as C++, Python, or Go - Have strong systems fundamentals across networking, operating systems, distributed systems, or infrastructure engineering - Are motivated by building infrastructure that directly accelerates frontier AI research and deployment About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportu

ABOUT THE TEAM The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. ABOUT THE ROLE As a researcher working on Frontier Evals & Environments, you will help build north star model environments to drive progress towards safe AGI/ASI. Your work will directly guide the research programs of the most ambitious training runs happening at OpenAI. Some prior open-sourced evaluations built by researchers in this role include GDPval https://openai.com/index/gdpval/, SWE-bench Verified https://openai.com/index/introducing-swe-bench-verified/, MLE-bench https://openai.com/index/mle-bench/, PaperBench https://openai.com/index/paperbench/, and SWE-Lancer https://openai.com/index/swe-lancer/. If you are interested in feeling firsthand the fast progress of our models, and steering them towards good outcomes, this is the role for you. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. IN THIS ROLE, YOU MIGHT - Create ambitious RL environments to push our models to their limits, and measure frontier model capabilities, skills, and behaviors - Develop new methodologies for automatically exploring the behavior of these models - Dive deep into the science of measurement, including understanding scalability, reliability, and variance of our evaluation methodology - Help steer training for our largest training runs, and see the future first - Design scalable systems and processes to support continuous evaluation - Build self-improvement loops to automate model understanding YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to work with. - Can move from a vague behavioral problem to a concrete experiment: define the hypothesis, build the pipeline, run the model, analyze the result, and decide what to do next. - Are comfortable working across research, product, infrastructure, data, evals, and safety boundaries, and can communicate clearly with each group. - Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous. - Want to train and ship the models that make agents genuinely useful for developers, enterprises, researchers, and everyday users. Abo

ABOUT THE TEAM The Workload team is responsible for designing and running OpenAI’s LLM training and inference infrastructure that powers frontier models at massive scale. Our systems unify how researchers train and serve models, abstracting away the complexity of performance, parallelism, and execution across vast GPU/accelerator fleets. By providing this foundation, the Workload team ensures that researchers can focus on advancing model capabilities while we handle the scale, efficiency, and reliability required to bring those models to life. ABOUT THE ROLE We are looking for an engineer to design and implement the dataset infrastructure that powers OpenAI’s next-generation training stack. You will be responsible for building standardized dataset interfaces, scaling pipelines across thousands of GPUs, and proactively testing performance bottlenecks. In this role, you will collaborate closely with the multimodal researchers, and other infra groups to ensure datasets are unified, efficient, and easy to consume. IN THIS ROLE, YOU WILL: - Design and maintain standardized dataset APIs, including for multimodal (MM) data that cannot fit in memory. - Build proactive testing and scale validation pipelines for dataset loading at GPU scale. - Collaborate with teammates to integrate datasets seamlessly into training and inference pipelines, ensuring smooth adoption and a great user experience. - Document and maintain dataset interfaces so they are discoverable, consistent, and easy for other teams to adopt. - Establish safeguards and validation systems to ensure datasets remain reproducible and unchanged once standardized. - Debug and resolve performance bottlenecks in distributed dataset loading (e.g., straggler systems slowing global training). - Provide visualization and inspection tools to surface errors, bugs, or bottlenecks in datasets. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong engineering fundamentals with experience in distributed systems, data pipelines, or infrastructure. - Have experience building APIs, modular code, and scalable abstractions, while recognizing that abstractions ultimately serve the users and UX is an important part of the abstractions design. - Are comfortable debugging bottlenecks across large fleets of machines. - Take pride in building infrastructure that “just works,” and find joy in being the guardian of reliability and scale. - Are collaborative, humble, and excited to own a foundational (if not glamorous) part of the ML stack. Bonus points if you: - Have background knowledge in data math, probability, or distributed data theory. - Have worked with GPU-scale distributed systems or dataset scaling for real-time data About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Ch

By applying to this role, you will be considered for Research Engineer roles across all teams at OpenAI. About the Role As a Research Engineer here, you will be responsible for building AI systems that can perform previously impossible tasks or achieve unprecedented levels of performance. We're looking for people with solid engineering skills (for example designing, implementing, and improving a massive-scale distributed machine learning system), writing bug-free machine learning code, and building the science behind the algorithms employed. The most outstanding deep learning results are increasingly attained at a massive scale, and these results require engineers who are comfortable working in large distributed systems. We expect engineering to play a key role in most major advances in AI of the future. We expect you to: - Have strong programming skills - Have experience working in large distributed systems - Be excited about OpenAI’s approach to research Nice to have: - Interested in and thoughtful about the impacts of AI technology - Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

About the team The AI Deployment Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. This role is based in Paris. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. We require fluency in French for this role. About the role We are seeking a technically proficient, product-minded engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, helping them optimize their own systems and turning those learnings into durable improvements across OpenAI’s research and products. You will partner deeply on complex workflows, identify the gaps that matter, and help transform those gaps into reproducible evaluations, technical insights - helping shape OpenAI's research and product direction. This role is well suited to engineers who are equally comfortable debugging a workflow, iterating on prompts or agents, designing evaluations, and collaborating across research and product. You should be excited by ambiguous, high-impact problems and motivated by the opportunity to shape how advanced AI systems improve in practice. In this role, you will: - Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement. - Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer value. - Synthesize and deliver valuable feedback to the Product and Research teams, turning real usage patterns into clear, reproducible evals, benchmarks, and technical artifacts that improve model and product quality and ensure customer-grounded learnings influence roadmap and model development. - Build repeatable tools, patterns, and evaluation approaches that raise the quality bar across multiple use cases. - Operate with strong judgment in ambiguous environments, balancing immediate technical problem-solving with longer-term system improvement. - Build relationships within the startup ecosystem, serving as a technical partner to both individual customers and the broader community. You’ll thrive in this role if you: - Have strong software engineering & AI fundamentals. For example, experience as a startup CTO, software engineer, ML engineer, Data Scientist or equivalent. Experience shipping production systems end-to-end is a strong plus. - Have experience as a technical founder, or engineer at an early stage startup - Have familiarity with, or interest in, model training pipelines and reinforcement learning. - Have experience building AI applications, agents, or evaluation systems, and can reason clearly about model behavior in complex workflows. - Are comfortable working directly with highly technical users and translating their challenges into concrete technical signals. - Can move fluidly between prototyping, debugging, evaluation design, and cross-functional collaboration. - Communicate clearly across technical and non-technical audiences. - Bring high agency, strong product sense, and a bias toward building durable improvements rather than one-off fixes About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world throug

About the Team The Safety Systems team https://openai.com/safety/safety-systems is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society, and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Safety Oversight Research team aims to fundamentally advance our capabilities to maintain oversight over frontier AI models, and leverage these advances to ensure OpenAI’s deployed models are safe and beneficial. This requires a breadth of new ML research in the areas of human-AI collaboration, reasoning, robustness, and scalable oversight to keep pace with model capabilities. We invest heavily in developing novel model and system-level methods of identifying and mitigating AI misuse and misalignment. Our goal is to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. About the Role OpenAI is seeking a senior researcher with a passion for AI safety and experience in safety research. Your role will set directions for research to maintain effective oversight of safe AGI and work on research projects to identify and mitigate misuse and misalignment in our AI systems. You will play a critical role in defining how a safe AI system should look in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. In this role, you will: - Develop and refine AI monitor models to detect and mitigate known and emerging patterns of misuse and misalignment. - Set research directions and strategies to make our AI systems safer, more aligned, and more robust. - Evaluate and design effective red-teaming pipelines to examine the end-to-end robustness of our safety systems, and identify areas for future improvement. - Conduct research to improve models’ ability to reason about questions of human values, and apply these improved models to practical safety challenges. - Coordinate and collaborate with cross-functional teams, including T&S, legal, policy and other research teams, to ensure that our products meet the highest safety standards. You might thrive in this role if you: - Are excited about OpenAI’s mission https://openai.com/mission/ of building safe, universally beneficial AGI and are aligned with OpenAI’s charter https://openai.com/charter/ - Show enthusiasm for AI safety and dedication to enhancing the safety of cutting-edge AI models for real-world use. - Bring 4+ years of experience in the field of AI safety, especially in areas like RLHF, human-AI collaboration, fairness & biases. - Hold a Ph.D. or other degree in computer science, machine learning, or a related field. - Thrive in environments involving large-scale AI systems. - Possess 4+ years of research engineering experience and proficiency in Python or similar languages. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualifie

The Compute & Infrastructure Strategy team handles strategy and execution of OpenAI’s compute roadmap. This team’s key responsibilities span financial analysis & reporting, capacity planning, commercial and business development, and strategic partnerships. We partner across the business to allocate and deploy our resources for the highest impact outcomes. About the Role Compute is central to OpenAI’s roadmap and vision. We are seeking an Associate to support financial and strategic work across our compute and infrastructure portfolio. This is a finance generalist role that includes core FP&A responsibilities as well as investment analysis, commercial decision support, and strategic planning. You will own analyses and workstreams, partner closely with technical and finance teams, and help shape decisions about how OpenAI invests in and manages compute. In this role, you will be given direction on the objective and expected to independently structure the problem, work through incomplete information, and deliver a high-quality analysis and recommendation. In this role, you will: - Build and maintain financial models across different elements of compute, including GPUs, CPUs, storage, networking, data centers, and power - Support planning, forecasting, budgeting, reporting, and variance analysis across compute and infrastructure - Perform investment analysis and evaluate commercial decisions and strategic initiatives - Prepare high-quality analyses, recommendations, and Exec and Board-facing presentations - Support business partners across compute infrastructure, FP&A, and strategic finance - Help improve the team’s processes, tools, and ways of working, and identify opportunities for OpenAI to continue leading in compute You might thrive in this role if you have: - 3+ years of experience across private/growth equity, investment banking, or strategic finance, or 3+ years in a finance operating role at a high-growth technology company - Background in infrastructure, data centers, compute, cloud, semiconductors, or a related industry strongly preferred - Exceptional analytical, financial modeling, and written and verbal communication skills - Proven ability to learn quickly and succeed in unfamiliar operating environments - Comfort independently structuring ambiguous problems and working through incomplete information - Track record of producing high-quality work under ambitious deadlines - Effectiveness in multidisciplinary, cross-functional environments - Familiarity with data systems, analytical tools, and large datasets preferred but not required - Bachelor’s degree or equivalent practical experience; technical undergraduate degree preferred but not required About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California

About the Team OpenAI is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities - Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. - Review and develop basis-of-design documents, single-line diagrams, equipment specifications, commissioning plans, and power system studies including load flow, short circuit, protection coordination, arc flash, and grid transient compliance. - Lead technical evaluation of equipment vendors, manufacturers, design consultants, commissioning agents, contractors, and test labs. Review submittals, schematics, certifications, quality records, and test reports. - Evaluate AC and DC power distribution options for high-density compute, including rectifier architectures, busway, rack power shelves, power supplies, cable management, redundancy strategies, serviceability, and fault isolation. - Partner with mechanical, cooling, controls, hardware, networking, construction, and operations teams to ensure electrical systems support liquid-cooled GPU rack deployments and reliable facility operation. - Drive FAT, SAT, witness testing, burn-in, reliability testing, interoperability testing, and integrated systems testing for critical infrastructure and rack deployments. - Help guide and operate an R&D program to validate new equipment, rack designs, telemetry, operating envelopes, failure scenarios, and facility-to-hardware interactions. - Define telemetry and controls requirements including metering, waveform capture, breaker and relay status, UPS and battery health, generator status, rack power, CDU status, coolant conditions, alarms, and control states. - Analyze lab data, operational incidents, power quality events, nuisance trips, thermal excursions, controls alarms, and rack-level failures to improve designs, procedures, vendor quality, and reliability models. - Create engineering standards, test procedures, commissioning scripts, operating procedures, decision records, risk registers, and concise executive summaries. - Provide senior technical escalation support during design reviews, construction, manufacturing validation, commissioning, energization, deployment, and operational events. - Raise the t

About the Team OpenAI’s Platform and Infrastructure Engineering organization advances the mission of deploying artificial general intelligence (AGI) for the benefit of all by delivering secure, scalable, and resilient technology solutions. Our team builds and maintains robust infrastructure that safeguards OpenAI’s data and systems while ensuring employees are well-equipped and seamlessly connected. By prioritizing security, reliability, and user-centric solutions, we empower OpenAI employees to drive impactful AI research, corporate operations, and product innovation. About the Role As a Software Engineer: Internal Applications, Enterprise, you will build internal products that make technology support and administration safer, faster, and less dependent on manual intervention. You will help reduce reliance on broadly privileged human actions, turn recurring technology problems into paved paths, and build agentic systems that can help resolve tickets end to end. A core part of the role is building the interfaces that bring employees, AI agents, and human responders together in a shared ITSM experience, with the right context, controls, and handoffs at each step. We are seeking engineers who enjoy working across frontend and backend layers on ambiguous, high-leverage enterprise problems. You should bring strong product judgment, solid backend engineering fundamentals, and an interest in building software that changes how technology support, system administration, and agent-assisted operations are delivered. The best fit will care as much about the quality of the operator and employee experience as the correctness of the backend systems behind it. In this role, you will: - Build frontend experiences that let employees request help, let agents gather context and take safe actions, and let human responders review, approve, or take over without losing the thread. - Reduce reliance on broadly privileged manual actions by replacing them with narrow, auditable, policy-aware automation. - Turn recurring technology support and administration problems into paved-path processes that can be completed consistently and, where appropriate, without a human in the loop. - Build agentic solutions that can understand tickets, gather context, execute safe actions, and escalate intelligently when automation is not enough. - Improve ITSM experiences across intake, routing, execution, handoff, and auditability. - Create reusable tools, APIs, and execution primitives that agents and operators can use safely across enterprise systems. - Design internal applications that pair strong frontend usability with robust backend systems, especially for complex operational tasks. - Partner closely with IT, Security, and business teams to identify where software can remove friction, reduce risk, and improve operational leverage. - Work with IAM and Security partners to ensure internal applications align with Zero Trust principles, RBAC expectations, and compliance needs. - Build backend foundations that support secure products across identity, ITSM, ticketing, and service integrations. - Strengthen monitoring, observability, and incident readiness for the systems behind these experiences. - Manage multiple initiatives while maintaining a high bar for usability, implementation quality, and operational follow-through. You may be right for this role if you have: - Strong experience building production software across both frontend and backend layers, with particular strength in modern frontend development. - Experience designing interfaces for complex operational products, internal tools, or case-management systems. - A track record of turning ambiguous operational problems into clear, usable products or systems. - Solid backend engineering fundamentals in API design, data modeling, integrations, and system reliability. - Experience building internal platforms, support tooling, automation systems, or operational products. - Interest in agentic systems, ITSM, enterpr

About the Team The Technical Success team is responsible for ensuring the safe and effective deployment of ChatGPT and OpenAI API applications for developers and enterprises. We act as a trusted advisor and thought leader for our customers, ensuring developers and enterprises maximize value from our models and products. As a Solutions Engineer you’ll help our customers transform their business through solutions such as customer service, automated content generation, and novel applications that make use of our newest, most exciting models. About the Role We are seeking a solutions engineer to partner with our customers and ensure they achieve tangible business value from our models through ChatGPT and the OpenAI API. You will partner with senior business stakeholders to understand their pre-sales needs, guide their AI strategy, and identify the highest value use cases and applications. You will work with business and technical teams to demonstrate the value of our solutions and recommend architectural patterns to kickstart their implementation and development. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Deliver an exceptional pre-sales customer experience for prospects and customers by providing technical expertise, outlining the value proposition, and answering product, API, and LLM-related questions. - Demonstrate how leveraging OpenAI APIs and ChatGPT can meet customers’ business needs and deliver substantial business value. This includes building and presenting demos, scoping use cases, recommending architecture patterns, and providing in-depth technical advisory. - Create and maintain documentation, guides, and FAQs related to common questions and requirements discovered during the pre-sales process. - Develop and nurture strong customer relationships during the evaluation, validation, and purchasing process. - Foster customer advocacy and represent the voice of the customer with internal teams by gathering and relaying customer feedback, identifying themes across customers, and incorporating them into product planning. - Serve as the first line of defense for security and compliance questions, explaining standardized collateral, guiding customers toward relevant resources (e.g., trust portal), and escalating complex requirements to the appropriate teams. You’ll thrive in this role if you: - Have 3+ years of experience in a technical pre-sales or similar role, managing C-level technical and business relationships with complex global organizations. - Demonstrate a thorough understanding of IT security principles and customer requirements for technical B2B SaaS products, with experience providing higher-level security and compliance support. - Have foundational training in programming languages like Python or Javascript. - Have delivered prototypes of Generative AI/traditional ML solutions and have knowledge of network/cloud architecture. - Are an effective presenter and communicator who can translate business and technical topics to all audiences, including senior leaders. - Own problems end-to-end and are willing to pick up whatever knowledge you're missing to get the job done. - Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the bas

ABOUT THE TEAM The Interpretability team studies internal representations of deep learning models. We are interested in using representations to understand model behavior, and in engineering models to have more understandable representations. We are particularly interested in applying our understanding to ensure the safety of powerful AI systems. Our working style is collaborative and curiosity-driven. ABOUT THE ROLE OpenAI is seeking a researcher passionate about understanding deep networks, with a strong background in engineering, quantitative reasoning, and the research process. You will develop and carry out a research plan in mechanistic interpretability, in close collaboration with a highly motivated team. You will play a critical role in helping OpenAI ensure future models remain safe even as they grow in capability. This will make a significant impact on our goal of building and deploying safe AGI. In this role, you will: - Develop and publish research on techniques for understanding representations of deep networks. - Engineer infrastructure for studying model internals at scale. - Collaborate across teams to work on projects that OpenAI is uniquely suited to pursue. - Guide research directions toward demonstrable usefulness and/or long-term scalability. You might thrive in this role if you: - Are excited about OpenAI’s mission https://openai.com/about/ of ensuring AGI benefits all of humanity, and are aligned with OpenAI’s charter https://openai.com/charter/. - Show enthusiasm for long-term AI safety, and have thought deeply about technical paths to safe AGI. - Bring experience in the field of AI safety, mechanistic interpretability, or spiritually related disciplines. - Hold a Ph.D. or have research experience in computer science, machine learning, or a related field. - Thrive in environments involving large-scale AI systems, and are excited to make use of OpenAI’s unique resources in this area. - Possess 2+ years of research engineering experience and proficiency in Python or similar languages. - Are deeply curious. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to se

About the Team The Developer Experience team at OpenAI has a singular focus: empowering developers globally. Our mission is to provide every developer and startup on the planet with the most delightful and seamless experience to integrate AI into their applications and products. We ensure developers have the tools, resources, and support they need to unlock AI’s full potential. We create inspiring demos, developer tools, sample applications, and technical content that show developers how to build with Codex and frontier models like GPT-5.5 and GPT-Image-2 to create powerful agents and AI-native applications. We collaborate closely with product, engineering, research, and GTM teams to ensure the developer journey, from onboarding with Codex to first API call to production deployment, is seamless, effective, and delightful. About the Role As a Developer Experience Engineer, you will create compelling technical content, developer tools, and sample applications designed to inspire developers and enable them to succeed with Codex and OpenAI’s APIs and products for developers. You will engage with developers and technical founders, demonstrating best practices and building innovative applications powered by frontier models, multimodal capabilities, and tools like Codex. We’re looking for people who combine strong technical skills, creativity, and a passion for engaging with and empowering developers. In this role, you will: - Develop demos and sample applications that showcase best practices for building with Codex, frontier models, multimodal capabilities, and agents. - Create high-quality technical content—including tutorials, blog posts, videos, and code samples—to educate and inspire the developer community about our models, APIs, and Codex. - Actively engage with and foster a vibrant local and global developer ecosystem around OpenAI’s platform and products. - Represent OpenAI at developer events and online, serving as a knowledgeable and approachable advocate for developers. - Gather and synthesize developer feedback to inform and improve our product roadmap. - Collaborate cross-functionally with product, engineering, and marketing teams to drive adoption and success across OpenAI’s developer products, including Codex and our APIs. - Contribute directly to improving and refining OpenAI’s developer products, interfaces, and surfaces. - Own challenges end-to-end, proactively closing gaps and developing new skills to solve complex problems. You might thrive in this role if you: - Are passionate about crafting exceptional developer experiences and creating inspirational technical content and projects. - Bring a robust full-stack engineering background with demonstrated experience building innovative applications using AI and large language models (LLMs). - Have strong user empathy and care deeply about delivering experiences developers truly appreciate. - Have a proven track record of successfully creating engaging technical content, compelling demos, or innovative developer tooling that accelerates technology adoption. - Find joy in coding, continuously shipping high-quality, impactful software. - Excel in dynamic environments characterized by rapidly evolving priorities, ambiguity, and competing deadlines. - Are an exceptional collaborator who thrives working cross-functionally and enjoys partnering with diverse teams. - Maintain a genuine commitment to AI ethics and safety, strongly aligning with OpenAI's responsible AI development principles. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that for

About the Team The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. Our mission is to push the frontier of code generation and agentic reasoning, and deploy these capabilities in real-world products such as ChatGPT and the API, as well as in next-generation tools specifically designed for agentic coding. We operate across research, engineering, product, and infrastructure—owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. About the Role As a Performance & Systems Engineer on the Codex team, you will be responsible for whole-system optimization across a complex, evolving stack. Codex spans LLM inference, cloud orchestration, agentic work management, and multiple product surfaces. Your job will be to identify and land high-leverage changes—across infrastructure, modeling, and product layers—that make Codex agents significantly faster and cheaper to serve. We’re looking for generalists who thrive in ambiguity and love chasing performance bottlenecks to ground. This is a high-ownership role where your work will directly improve the experience of millions of users. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Hunt down and address inefficiencies across the Codex system stack, from agent behavior to LLM inference to container orchestration, and beyond. - Build tooling to measure, profile, and optimize system performance at scale. - Collaborate with researchers and engineers to land high-ROI changes that improve latency and cost. You might thrive in this role if you: - Have experience operating across both ML systems and cloud infrastructure. - Enjoy diving into messy, ambiguous problems and emerging with clear wins. - Think holistically about performance, balancing speed, cost, and user experience. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected informa

About The Team The Data Understanding team is responsible for creating the high quality datasets and their quantized representation for OpenAI. This includes synthesizing data, building VQ representations, and processing, filtering, deduplication, quality control, and tokenization so it can be used effectively in big model training runs. About The Role We're looking to advance how OpenAI builds and understands pretraining data at scale. You'll treat data quality and curation as core research problems: developing new methods to select, combine, and transform data; creating datasets that improve model capabilities; and designing rigorous experiments to understand how data choices and interventions affect model learning and downstream behavior. You'll work closely with frontier models and web-scale data to build evidence for which approaches work and why, then translate successful research into scalable data processing pipelines We Expect You To - Have a strong track record of new or improved ML ideas, through publications, projects, or applied research. - Own and drive a research agenda, from choosing the right problems to carrying long-running work through to impact. - Be excited by OpenAI’s empirical, collaborative approach to research. Nice To Have - Thoughtfulness about AI’s impact, including privacy, provenance, and data quality. - Experience building high-performance deep learning or large-scale data processing systems. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/globa

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and support next-generation infrastructure design. About the Role We are seeking an Performance Modeling Engineer to support the development and application of modeling tools used to evaluate AI system performance and inform architectural decisions. In this role, you will partner closely with Senior Performance Modeling Engineers and the Performance Modeling Lead to analyze system behavior, run simulations and analytical models, and help evaluate tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks while developing a strong foundation in system architecture and AI infrastructure. This role is ideal for early-career engineers with 1–2 years of experience in software engineering, systems analysis, or performance modeling who are excited to grow in large-scale infrastructure and hardware/software systems. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities - Support the development and maintenance of performance modeling tools and frameworks - Assist in building models to evaluate system behavior across compute, memory, networking, and interconnect subsystems - Help analyze distributed system scaling behavior and identify performance bottlenecks - Run simulations and analytical models to support architecture and infrastructure decisions - Partner with senior engineers to evaluate design tradeoffs across hardware and system components - Interpret modeling outputs and help translate findings into clear recommendations - Validate models using benchmarking data and real system performance measurements - Improve modeling workflows, documentation, and usability for broader team adoption - Collaborate cross-functionally with hardware, infrastructure, and architecture teams - Continuously build technical depth across AI infrastructure, system architecture, and performance analysis Qualifications - 1–2 years of experience in software engineering, systems modeling, performance analysis, or related technical work - Strong programming skills and experience building technical tools, scripts, or frameworks - Familiarity with system architecture fundamentals such as compute, memory, and networking - Ability to reason about system performance, bottlenecks, and scaling behavior - Strong analytical and problem-solving skills with comfort working in quantitative environments - Ability to learn quickly and work effectively across technical teams Preferred Skills - Exposure to AI/ML workloads, distributed systems, or large-scale infrastructure - Experience with simulation tools, benchmarking, profiling, or performance analysis - Familiarity with data center systems, server architecture, or hardware platforms - Interest in system architecture and hardware/software co-design - Internship or early professional experience in performance engineering, infrastructure, or systems design About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion,

About the Team OpenAI’s Infrastructure organization builds and evaluates the systems that power advanced AI workloads. We work closely with hardware, modeling, and architecture teams to ensure that new platforms deliver real-world performance aligned with workload needs. Our team focuses on understanding workload behavior across evolving hardware platforms—bridging the gap between theoretical capability and observed system performance. About the Role We are seeking a Workload Porting & Performance Engineer to evaluate new hardware platforms by porting benchmarks and real-world workloads, analyzing performance, and identifying system bottlenecks. In this role, you will bring up workloads on new systems, characterize performance behavior, and adapt workloads to better utilize hardware capabilities. You will play a critical role in validating new platforms and ensuring that performance aligns with expectations across compute, memory, and networking subsystems. This role requires strong hands-on experience with performance analysis, workload optimization, and system-level debugging across hardware and software boundaries. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities - Port and enable benchmarks and real-world workloads on new hardware platforms. - Evaluate system performance across compute, memory, storage, and networking subsystems. - Identify and analyze performance bottlenecks and inefficiencies. - Adapt and optimize workloads to better utilize hardware capabilities. - Develop and run performance experiments and profiling workflows. - Compare expected vs. observed performance and provide feedback to: - hardware architecture teams - performance modeling teams - system and software engineers. - Debug issues across the stack, including software, runtime, and hardware interactions. - Provide actionable insights to guide platform readiness and deployment decisions. Qualifications - Experience with performance analysis, benchmarking, or workload optimization. - Strong understanding of system architecture, including CPU/GPU, memory, and I/O subsystems. - Experience porting or adapting workloads across different hardware platforms. - Familiarity with profiling tools and performance debugging techniques. - Ability to identify root causes of performance issues across hardware/software boundaries. - Experience working in large-scale or distributed system environments. Preferred Skills - Experience with AI/ML workloads, including training or inference systems. - Familiarity with GPU or accelerator-based systems. - Experience working with low-level performance tools (profilers, tracing, microbenchmarks). - Background in systems software, compilers, or runtime optimization. - Experience collaborating with hardware and architecture teams on performance validation. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or convict

About the Team Our Safety Systems https://openai.com/safety/safety-systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role If you have a specific expertise or speciality related to this work, please note it in your application via your resume, cover letter or application note. Frontier AI systems are expanding what people can do across domains, creating both enormous opportunities and difficult safety questions: when should a model help, when should it refuse, and how do we make those boundaries clear enough to train, evaluate, and enforce? In this role, you will help define how OpenAI’s models should behave in high-risk or high-ambiguity contexts, such as agentic systems, multimodal systems, user safety, privacy, and other emerging risk domains. This is an ideal role for someone who can move across unfamiliar topics, reason from first principles, and turn ambiguity into practical model behavior. You will work closely with research, engineering, product, preparedness, and operations teams to build policies that are technically grounded, measurable, and responsive to real-world risk. In this role, you will: - Design and maintain model policies across safety-relevant domains, including dual-use, agentic, and emerging frontier-risk areas. - Translate risk and harm models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level safeguards. - Define practical boundaries between beneficial uses of AI and assistance that could materially enable harm, exploitation, misuse, or unsafe outcomes. - Build policy artifacts that support model training, evaluation, and deployment.Partner with safety researchers, engineers, product teams, and other stakeholders to operationalize policy into scalable model behavior and measurable safeguards. - Use red-teaming results, deployment data, model failures, over-refusals, under-refusals, and ambiguous edge cases to improve policy and evaluation quality over time. - Identify emerging capability areas where frontier AI systems could create new safety challenges or lower barriers to harm. - Study real-world deployments to identify where model behavior succeeds, fails, or drifts from the intended safety posture. - Combine longer-horizon safety research with hands-on launch and deployment work. - Contribute to system cards, safety reports, policy documentation, launch reviews, and external communications on OpenAI's approach to model safety and risk mitigation. - Design and run human data campaigns, including gold set construction, labeling guidance, calibration, adjudication, and eval coverage analysis, to ensure policies can be reliably measured and improved. You might thrive in this role if you: - Have strong judgment about how advanced AI systems may affect real-world risk, especially in ambiguous, fast-moving, or high-impact areas. - Have experience building or applying policies, taxonomies, harm models, threat models, or risk frameworks for complex technical, social, or adversarial systems. - Can move across domains without needing to be the deepest subject-matter expert in every area, while knowing when to seek expert input. - Can turn fuzzy questions into structured policy frameworks, evaluation criteria, operational guidance, and enforceable model behavior. - Are comfortable using empirical evidence, including evaluations, red-teaming results, deployment observations, and model failure modes, to inform policy decisions. - Think in systems across policy, data, graders, classifiers, training, deployment safeguards, measurement, monitoring, and

About the team The Safety Systems team https://openai.com/safety/safety-systems is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Trustworthy AI team works on action relevant or decision relevant research to ensure we shape A(G)I keeping societal impacts in mind. This includes work on full stack policy problems such as building methods for public inputs into model values and understanding impacts of anthropomorphism of AI. We aim to translate nebulous policy problems to be technically tractable and measurable. We then use this work to inform and build interventions that increase societal readiness for increasingly intelligent systems. Our team also works on external assurances for AI with an aim for increasing independent checks and forming additional layers of validation. About the role We are looking to hire exceptional research scientists/engineers that can push the rigor of work needed to increase societal readiness for AGI. Specifically, we are looking for those that will enable us to translate nebulous policy problems to be technically tractable and measurable. This role is based in our San Francisco HQ. We offer relocation assistance to new employees. In this role, you will enable: - Set research and strategies to study societal impacts of our models in an action-relevant manner and figure out how to tie this back into model design - Build creative methods and run experiments that enable public input into model values - Increasing rigor of external assurances by turning external findings into robust evaluations - Facilitating and growing our ability to effectively de-risk flagship model deployments in a timely manner You might thrive in this role if you: - Are excited about OpenAI’s mission of building safe, universally beneficial AGI and are aligned with OpenAI’s charter - Demonstrate a passion for AI safety and making cutting-edge AI models safer for real-world use. - Possess 3+ years of research experience (industry or similar academic experience) and proficiency in Python or similar languages - Thrive in environments involving large-scale AI systems and multimodal datasets - Enjoy working on large-scale, difficult, and nebulous problems in a well-resourced environment - Exhibit proficiency in the field of AI safety, focusing on topics like RLHF, adversarial training, robustness, LLM evaluations - Have past experience in interdisciplinary research - Show enthusiasm for socio-technical topics About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act,

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage. In this role, you will: - Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response. - Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (coverage, precision, latency), tuning processes, and safe rollout patterns. - Automate response and investigations by building workflows that reduce toil (triage, enrichment, containment, evidence capture) and improve time-to-understand/time-to-contain. - Partner with other Security teams and system/infrastructure owners across the company to ensure new systems ship with the right telemetry, threat models, and response playbooks from day one. - Define D&R requirements and drive visibility across endpoints, identity, SaaS, cloud, Kubernetes: identify telemetry/control gaps, prioritize them, and advocate for fixes with partner teams (and implement directly when it’s the fastest/most effective path). - Evaluate and respond to emergent security concerns in a frontier AI lab environment, such as detection and response strategies for agents operating across infrastructure at scale. You might thrive in this role if you: - Have hands-on threat detection and/or incident response experience, including building detections, running investigations, and improving operational playbooks. - Understand modern adversary tradecraft (TTPs) and can translate it into practical detection strategies and response actions. - Bring a threat modeling mindset. You can evaluate new infrastructure or features, identify D&R implications (what could go wrong, what we’d need to see, how we’d respond), and turn that into concrete requirements for teams shipping the system. - Have experience working in Kubernetes/containerized environments, including building detections from cluster telemetry and understanding common failure and attack modes (workloads, nodes, control plane, networking). - Are comfortable reasoning about lower-level infrastructure and datacenter risks, such as firmware/BMC surfaces, network segmentation/telemetry, and hard-to-observe control paths. - Have experience across major cloud platforms (Azure, AWS, GCP, OCI), and can design cloud-agnostic detection approaches where possible. - Like building automation that replaces repetitive D&R work, including thoughtfully using agent-style workflows where they meaningfully reduce toil, while keeping outcomes measurable, auditable, and safe. - Are energized by new problem areas at a forward-leaning technology company: e.g., thinking through how to detect and respond to agents operating across systems at scale, and turning those ideas into pragmatic telemetry and response requirements. - Communicate clearly and collaborate well across teams.

By applying to this role, you will be considered for Research Scientist roles across all teams at OpenAI. About the Role As a Research Scientist here, you will develop innovative machine learning techniques and advance the research agenda of the team you work on, while also collaborating with peers across the organization. We are looking for people who want to discover simple, generalizable ideas that work well even at large scale, and form part of a broader research vision that unifies the entire company. We expect you to: - Have a track record of coming up with new ideas or improving upon existing ideas in machine learning, demonstrated by accomplishments such as first author publications or projects - Possess the ability to own and pursue a research agenda, including choosing impactful research problems and autonomously carrying out long-running projects - Be excited about OpenAI’s approach to research Nice to have: - Interested in and thoughtful about the impacts of AI technology - Past experience in creating high-performance implementations of deep learning algorithms About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global Applicant Privacy Policy https://cdn.openai.com/policies/global-employee-and-contractor-privacy-policy.pdf At OpenAI, we believe artificial intelligence has the potential to help people solve immense global challenges, and we want the upside of AI to be widely shared. Join us in shaping the future of technology.

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: - Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. - Build and maintain the load, chaos and synthetic testing software leveraged by development teams to make the systems they design and operate more reliable. - Build and maintain automation tools to streamline repetitive tasks and improve system reliability. - Build and maintain the platform for CPU/storage, GPU, and network lifecycle management to drive efficiency, accountability and support dynamic optimization of our resources. - Implement fault-tolerant and resilient design patterns to minimize service disruptions. - Develop and maintain service level objectives (SLOs) and service level indicators (SLIs) to measure and ensure system reliability. - Partner with researchers, engineers, product managers, and designers to bring new features and research capabilities to the world. - Participate in an on-call rotation to respond to critical incidents and ensure 24/7 system availability. You might thrive in this role if you: - Have a track record of accelerating engineering reliability by empowering your fellow engineers with excellent tooling and systems. - Have a humble attitude, an eagerness to help your colleagues, and a desire to do whatever it takes to make the team succeed. - Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. - Enjoy seeking out and addressing bottlenecks and areas for performance improvement in our systems. - Utilize Infrastructure as Code (IaC) principles to automate infrastructure provisioning and configuration management. - Are experienced in collaborating with cross-functional teams to ensure that reliability and scalability are considered in the design and development of new features and services. Qualifications: - Bachelor's degree in Computer Science, Information Technology, or a related field (or equivalent work experience). - Proven experience as an SWE focused on reliability or a similar role in a fast-paced, rapidly scaling company. - Strong proficiency in cloud infrastructure. - Proficiency in programming languages. - Experience with containerization technologies and container orchestration platforms like Kubernetes. - Knowledge of IaC tools such as Terraform or CloudFormation. - Excellent problem-solving and troubleshooting skills. - Strong communication and collaboration skills. - Experience with observability tools such as DataDog, Prometheus, Grafana and Splunk. - Experience with microservices architecture and service mesh techno

About the Team The Future of Computing Research team is an applied research team within the Consumer Devices group focused on developing new methods, models, and evaluation frameworks that support our vision for the future of computing. We work at the frontier of multimodal AI, helping turn emerging model capabilities into product experiences that are useful, delightful, and worthy of long-term trust. Our work explores a new class of AI systems that can learn over time, adapt to individuals, and support people in the flow of daily life. This includes long-term memory, user modeling, and personalization systems that are aligned not just with immediate satisfaction, but with a person’s broader goals, values, and well-being. We work closely across research, engineering, design, product, and safety to define what it means to build AI systems that know you over time, act at the right moment, and help in ways that are context-aware, respectful, and demonstrably beneficial. About the Role We are looking for a Research Engineer / Scientist to join the Future of Computing Research team to work on RLHF and post-training for personalized, multimodal AI systems. This role will focus on building the learning and evaluation foundations that help models become more context-aware, adaptive, and useful over time. You will work on problems such as reward modeling, preference learning, long-horizon evaluation, and policy improvement for systems that must make high-quality behavioral decisions in realistic user settings. The work is deeply product-grounded: success is not just higher benchmark performance, but better model behavior in real-world use. The ideal candidate is excited about pushing beyond one-turn assistant behavior toward systems that improve through feedback, learn from richer signals, and are trained against meaningful notions of user value. Internally, that maps closely to the need for careful reward design, feedback loops, and evaluation frameworks that test whether interventions are actually beneficial over longer horizons. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Develop RLHF and post-training methods for multimodal models. - Build reward models and preference-learning pipelines for adaptive, personalized model behavior. - Design datasets, rubrics, and evaluation frameworks that capture user preferences, contextual appropriateness, and long-term value in realistic tasks. - Run experiments on policy improvement using explicit feedback, implicit signals, and model-based grading. - Work on long-horizon evaluation problems, where model quality depends not just on a single response but on whether behavior improves outcomes over time. - Collaborate closely with safety researchers to ensure that adaptation and personalization remain aligned, interpretable, and bounded by clear constraints. - Prototype and iterate quickly on training recipes, reward formulations, data pipelines, and evaluation suites for product-relevant behaviors. - Help define how OpenAI measures success for personalized AI systems including trust, appropriateness, and long-term user benefit. You might thrive in this role if you: - Have a strong background in machine learning research, with experience in RLHF, reward modeling, preference optimization, or post-training for large models. - Have worked on one or more of: reinforcement learning, ranking, recommender systems, personalization, memory, or human-in-the-loop evaluation. - Care about rigorous empirical work and know how to design clean experiments, reliable evals, and decision-useful metrics. - Are excited by the challenge of training models against nuanced behavioral objectives. - Have experience building datasets or eval pipelines grounded in human preferences, rubrics, or real-world product behavior. - Are comfortable working across the stack, from data generation and labe

About the Team The Online Data team builds and operates the core online database and indexing services for OpenAI’s production AI applications, including supporting the explosive growth of ChatGPT, the #1 AI app in the world, and Codex, the fastest growing agentic development toolset in the world. Our mission is to ensure the reliability, correctness, and scalability of our online data stack and to curate a comprehensive portfolio of services that matches the relentless ambition of OpenAI, enabling our product and research teams to build 0-100 without getting bogged down in the minutiae of multi-region, multi-cloud, exabyte-scale data infrastructure. About the Role We are seeking an Engineering Manager to lead our Online Data Systems team, responsible for our in-house database and indexing technology. This role is about shepherding a team of world-class engineers tasked with building and operating hyperscale data storage and retrieval technology. You’ll be overseeing the delivery of extremely challenging engineering work in areas like distributed query execution, multi-region federation, self-orchestrating and self-healing services, low-level performance optimization, and more. There are few companies in the world building this kind of technology in-house at this scale where you’ll still be getting in on the ground floor. Instead of being a cog in the machine spending months chasing small optimizations, you’ll play a major part of shaping our future. In this role, you will: - Build, lead, and grow high-performing infrastructure engineering teams. - Drive the evolution of OpenAI’s in-house online data technologies, our core, hyper-scale database systems, indexing technologies, and vector search. - Anchor delivery around measurable reliability goals (SLOs, etc) to ensure system performance and resiliency is above reproach. - Champion pragmatic use of agent technology to amplify execution velocity. - Reduce operational toil and incident frequency through better abstractions, guardrails, and self-healing systems. You might thrive in this role if you: - Have a truly insatiable spirit for operational excellence, demonstrated by having your hands-on in building and operating infrastructure with strict reliability, latency, and security requirements. - Have experience managing data-intensive software engineering teams in intense, demanding environments. - Bring deep hands-on understanding of database, indexing, storage, and distributed systems technologies. - Effectively modulate your technical engagement to create space for a highly technical team to lead and grow. - Have a demonstrable track record of hiring, developing, and retaining senior engineers. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chanc

About the Team Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role As a Security Engineer on Detection & Response, you’ll help protect OpenAI’s most sensitive assets– including our intellectual property, customer data, and the infrastructure that supports them– by building and operating the systems we use to detect suspicious activity and respond effectively when it matters. You’ll work across endpoints, identity, cloud, hyperscale compute infrastructure, and datacenter-adjacent layers, partnering closely with security teams and infrastructure owners to define the telemetry and response requirements we need and building tooling and automation where it delivers the most leverage. In this role, you will: - Build and evolve Detection & Response capabilities across OpenAI’s infrastructure, products, and research environments, with an emphasis on high-signal detection and reliable operational response. - Engineer detection pipelines and tooling: develop rule lifecycle management, measurement/quality loops (coverage, precision, latency), tuning processes, and safe rollout patterns. - Automate response and investigations by building workflows that reduce toil (triage, enrichment, containment, evidence capture) and improve time-to-understand/time-to-contain. - Partner with other Security teams and system/infrastructure owners across the company to ensure new systems ship with the right telemetry, threat models, and response playbooks from day one. - Define D&R requirements and drive visibility across endpoints, identity, SaaS, cloud, Kubernetes: identify telemetry/control gaps, prioritize them, and advocate for fixes with partner teams (and implement directly when it’s the fastest/most effective path). - Evaluate and respond to emergent security concerns in a frontier AI lab environment, such as detection and response strategies for agents operating across infrastructure at scale. You might thrive in this role if you: - Have hands-on threat detection and/or incident response experience, including building detections, running investigations, and improving operational playbooks. - Understand modern adversary tradecraft (TTPs) and can translate it into practical detection strategies and response actions. - Bring a threat modeling mindset. You can evaluate new infrastructure or features, identify D&R implications (what could go wrong, what we’d need to see, how we’d respond), and turn that into concrete requirements for teams shipping the system. - Have experience working in Kubernetes/containerized environments, including building detections from cluster telemetry and understanding common failure and attack modes (workloads, nodes, control plane, networking). - Are comfortable reasoning about lower-level infrastructure and datacenter risks, such as firmware/BMC surfaces, network segmentation/telemetry, and hard-to-observe control paths. - Have experience across major cloud platforms (Azure, AWS, GCP, OCI), and can design cloud-agnostic detection approaches where possible. - Like building automation that replaces repetitive D&R work, including thoughtfully using agent-style workflows where they meaningfully reduce toil, while keeping outcomes measurable, auditable, and safe. - Are energized by new problem areas at a forward-leaning technology company: e.g., thinking through how to detect and respond to agents operating across systems at scale, and turning those ideas into pragmatic telemetry and response requirements. - Communicate clearly and collaborate well across teams.

About the Team Our Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role We’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: - Perform engineering efforts focused on improving model serving, inference performance, and system efficiency - Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability - Partner closely with research and product teams to ensure our models perform effectively at scale - Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: - Have deep expertise in model performance optimization, particularly at the inference layer - Have a strong background in kernel-level systems, data movement, and low-level performance tuning - Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads - Can navigate ambiguity, set technical direction, and drive complex initiatives to completion This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data se

About the team GTM Growth Engineering builds product systems that help OpenAI's go-to-market organization scale with better signal, faster learning, and more leverage. We work in live GTM workflows where agents and humans together identify important customer moments, recommend or take the next action, route judgment-heavy work, and measure whether the workflow improved business outcomes. The Learning Experiences pod sits inside GTM Growth Engineering. Its focus is helping users and organizations build practical AI literacy and confidence inside OpenAI products: contextual guidance, hands-on practice, feedback, progress, re-entry, and clear next steps. About the role We're looking for a product engineer to help build learning experiences directly inside OpenAI products that drive user acquisition, activation, retention, and more meaningful use of AI. You will turn ambiguous product and learning goals into polished, reliable, user-facing experiences that help people learn by doing. You will own meaningful product slices end to end: interaction design details, frontend implementation, backend APIs and services, progress/state, content and runtime integration, telemetry, and launch readiness. The role is ideal for a strong product engineer who can connect product craft to measurable outcomes, with an added spike in education, learning science, coaching, assessment, onboarding, training, enablement, or AI literacy. What You'll Do - Build end-to-end product experiences that help users learn AI through real tasks inside OpenAI products. - Own full-stack product slices from prototype through launch, hardening, instrumentation, and iteration. - Create intuitive flows for onboarding, guided modules, practice, knowledge checks, feedback, progress, re-entry, and recommended next steps. - Build product flows that respond to a user's starting point and avoid one-size-fits-all learning paths. - Partner with product, design, content, research, data, customer-facing, safety, privacy, support, and go-to-market teams to ship trustworthy learning experiences. - Turn learning goals into clear product flows, reusable UI patterns, and product metrics we can improve. - Instrument the experience so we can understand usage, friction, completion, learning signals, and product quality. - Connect learning experiences to real product usage, user feedback, and operational signals so the product improves as it scales. - Make pragmatic tradeoffs across speed, quality, scalability, and operational simplicity in a 0-to-1 product area. What We're Looking For - Have 4+ years of experience as a software, product, or full-stack engineer building high-quality user-facing products. - Strong product judgment and a track record of turning ambiguous ideas into shipped product. - Strong frontend or full-stack engineering skills, with comfort across modern web apps, APIs, data models, stateful user flows, and instrumentation. - Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success metrics are still being discovered. - A high bar for UX quality, interaction details, accessibility, reliability, and user empathy. - Experience partnering closely with design, product, research, data, content, operations, and customer-facing stakeholders. - Ability to use qualitative feedback and product data to identify friction, prioritize work, and improve outcomes. - Clear written and verbal communication, especially when simplifying complex technical concepts for different audiences. - Careful judgment when building products that shape how users understand and use AI. You Might Thrive If - You like 0-to-1 product work where the right answer is discovered through shipping, measurement, and iteration. - You are excited by product surfaces that sit close to real users, real workflows, and measurable business outcomes. - You can move between prototype speed and production-quality engineering without losing sight of the user. - You enjoy

About the Team The Proactivity Research team, within OpenAI’s broader Personal AGI team, is focused on making our models in ChatGPT and future potential products proactive in ways that are truly useful. We're laying the technical foundations for AI that can anticipate what users need in real time, adapt as their goals and preferences shift, and build a deeper, evolving understanding of the person it's helping. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models’ personalization and agentic capabilities. Our team works on reinforcement learning, dataset creation, evaluations, and other post-training methods. We partner closely with research and product teams across the company to realize the vision of a highly personalized, collaborative, and proactive assistant. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own and pursue a research agenda to improve the proactivity and ability of our models to further user goals. - Build robust evaluations for tracking modeling improvements. - Design, implement, test, and debug code across our research stack. - Collaborate closely with the other research and product teams to influence the shape of technical solutions in the product You might thrive in this role if you: - Have a deep understanding of machine learning and machine learning applications. - Have a working knowledge of LLM post-training and evaluation approaches - Are passionate about, or have experience thinking about, personalization and enabling users to achieve their goals - Are comfortable diving into a large ML codebase to debug. - Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and relat

ABOUT THE TEAM The Industrial Compute team is responsible for building and scaling the infrastructure foundation that powers OpenAI’s research and products. The team works across compute strategy, infrastructure planning, hardware partnerships, and capacity management to ensure OpenAI can meet rapidly growing training and inference demands with resilient, efficient, and future-looking infrastructure systems. ABOUT THE ROLE As a Strategic Deals Leader, you will help shape OpenAI's long-term approach to AI infrastructure, compute capacity, and strategic ecosystem partnerships. Operating at the intersection of infrastructure strategy, technology evaluation, commercial partnerships, and market development, you will identify and execute opportunities that expand OpenAI's access to the compute, infrastructure, and technologies required to support frontier AI systems. You will work closely with engineering, infrastructure, finance, and executive leadership teams to evaluate emerging technologies, develop ecosystem strategies, assess build-versus-buy decisions, and cultivate strategic relationships across hardware vendors, cloud providers, data center operators, and the broader AI infrastructure ecosystem. We’re looking for people who combine deep understanding of AI infrastructure and emerging technology ecosystems with strong strategic judgment, technical curiosity, and the ability to build partnerships across a rapidly evolving industry landscape. IN THIS ROLE, YOU WILL - Develop and execute strategies that expand OpenAI's access to compute, infrastructure, and emerging AI technologies. - Evaluate strategic opportunities across hardware platforms, cloud providers, infrastructure partners, and ecosystem participants. - Partner with engineering and infrastructure teams to understand future workload requirements and translate them into long-term compute and ecosystem strategies. - Assess build-versus-buy tradeoffs across infrastructure, platform, and capacity decisions. - Build and manage relationships with hardware vendors, hyperscalers, cloud providers, data center operators, and emerging infrastructure companies. - Evaluate new infrastructure technologies and architectures to inform adoption, partnership, and deployment decisions. - Support commercial discussions and strategic partnerships that improve OpenAI's infrastructure flexibility, resilience, and long-term capacity position. - Monitor market, technology, and competitive developments across the AI infrastructure landscape and develop recommendations for leadership. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have experience in AI infrastructure, cloud computing, semiconductors, data centers, distributed systems, or adjacent technology ecosystems. - Possess a strong understanding of compute infrastructure, accelerator technologies, cloud platforms, and infrastructure economics. - Have experience evaluating emerging technologies and developing long-term infrastructure or ecosystem strategies. - Can work effectively with technical teams and translate complex engineering concepts into strategic business recommendations. - Have experience building partnerships and influencing senior stakeholders across internal and external organizations. - Demonstrate strong analytical and strategic thinking skills, with the ability to operate in ambiguous and rapidly evolving environments. - Communicate effectively with both technical and business audiences, including executive leadership. - Are passionate about the future of AI infrastructure and the ecosystem required to support frontier model development. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission

About the Team The ChatGPT Model Capabilities and Deployment team unified goal is to transform model advancements into great ChatGPT user experiences through reliable serving, rapid experimentation, safe deployment, and continuous improvement. Team Focus Areas - Model Experimentation: - Enable rapid, safe model validation for ChatGPT and Codex products through experiment automation and lifecycle management. - Model Deployment: - Ensure safe, scalable deployment of model capabilities with robust rollout and operational tooling. - Automate capacity management and incorporate platform-wide health monitors. - Model Measurement: - Build comprehensive evaluation and measurement systems for model quality, from user signals to launch scorecards. - Improve end-to-end feedback loops for continual model improvement. Key Partnerships Collaborate cross-functionally with teams including Model Measurement DS, Research, Codex, Fleet, Inference, and API. In this role, you will: - Elevate and consolidate ChatGPT’s harness, context management, and system prompt frameworks. - Drive expansion and improvement of multi-tier model experiences. - Support and scale self-serve experiment capabilities and automated guardrails. - Lead model rollout automation, capacity management, and health monitoring. - Shape end-to-end measurement systems (evals, grader signals, user feedback, etc.). You might thrive in this role if you have: - Proven experience leading engineering teams in complex, cross-functional environments. - Demonstrated success shipping production systems at scale (ideally for AI or large backend services). - Deep understanding of model-driven product development, deployment lifecycle, and measurement tooling. - Excellent communication and collaboration skills—experience interfacing directly with engineering, research, and product stakeholders. - Prior involvement with large language models, distributed infrastructure, or experimentation platforms is a plus. Why Work With Us - Tackle highly impactful technical challenges at the cutting edge of AI. - Collaborate with world-class researchers, engineers, and product leaders. - Build infrastructure and experiences used by millions. - Shape the future of how people interact with AI. If you’re passionate about advancing AI reliability, safety, and user impact at a global scale, we encourage you to apply! About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted t

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization, working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role You will own and execute long-term talent strategies to identify, engage, and recruit many of the world’s leading and emerging AI researchers, research engineers, and technical scientists working at the frontier of machine learning. This is not a traditional execution-focused recruiting role. You will operate as a strategic partner to OpenAI’s research staff, helping define hiring priorities, shape search strategy, influence candidate evaluation, and guide hiring decisions that directly impact the direction and quality of our frontier-model research and fulfillment of our mission. In this role, you will: - Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve. - Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist. - Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles. - Serve as a trusted advisor throughout candidate evaluation and closing — helping leaders calibrate for research excellence, long-term potential, and organizational fit. - Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains. You might thrive in this role if you: - Significant experience recruiting within highly technical or specialized environments. - Deep interest in AI research and a desire to engage directly with global research communities. - Experience recruiting within highly technical or specialized environments such as ML/AI, distributed systems, infrastructure, scientific computing, or quantitative research. - Track record of leading complex, ambiguous technical searches from early talent mapping through close. - Experience navigating high-stakes negotiations with senior technical or research candidates. - Comfort operating in fast-moving environments where hiring priorities and role definitions may evolve over time. Workplace & Location This role is based in our San Francisco office and we aren’t considering remote applications at this time. We use a hybrid work model of 3 days in the office with optional work from home on Thursdays and Fridays. We also offer relocation assistance to new employees. Our open-plan offices have height-adjustable desks, conference rooms, phone booths, well-stocked kitchens full of snacks and drinks, three in-house prepared meals daily, outdoor space for working and socializing, wellness rooms, private bike storage, and more. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional i

About the Team Data Platform at OpenAI owns the foundational data stack powering critical product, research, and analytics workflows. We operate some of the largest Spark compute fleets in production; design, and build data lakes and metadata systems on Iceberg and Delta with a vision toward exabyte-scale architecture; run high throughput streaming platforms on Kafka and Flink; provide orchestration with Airflow; and support ML feature engineering tooling such as Chronon. Our mission is to deliver reliable, secure, and efficient data access at scale and accelerate intelligent, AI assisted data workflows. Join us to build and operate these core platforms that underpin OpenAI products, research, and analytics. We’re not just scaling infrastructure – we’re redefining how people interact with data. Our vision includes intelligent interfaces and AI-assisted workflows that make working with data faster, more reliable, and more intuitive. About the Role This role focuses on building and operating data infrastructure that supports massive compute fleets and storage systems, designed for high performance and scalability. You’ll help design, build, and operate the next generation of data infrastructure at OpenAI. You will scale and harden big data compute and storage platforms, build and support high-throughput streaming systems, build and operate low latency data ingestions, enable secure and governed data access for ML and analytics, and design for reliability and performance at extreme scale. You will take full lifecycle ownership: architecture, implementation, production operations, and on-call participation. You’ve supported Spark, Kafka, Flink, Airflow, Trino, or Iceberg as platforms. You’re well-versed in infrastructure tooling like Terraform, experienced in debugging large-scale distributed systems, and excited about solving data infrastructure problems in the AI space. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security - Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient - Accelerate company productivity by empowering your fellow engineers & teammates with excellent data tooling and systems - Collaborate with product, research and analytics teams to build the technical foundations capabilities that unlock new features and experiences - Own the reliability of the systems you build, including participation in an on-call rotation for critical incidents You might thrive in this role if you: - Have 4+ years in data infrastructure engineering OR - Have 4+ years in infrastructure engineering with a strong interest in data - Take pride in building and operating scalable, reliable, secure systems - Are comfortable with ambiguity and rapid change - Have an intrinsic desire to learn and fill in missing skills, and an equally strong talent for sharing learnings clearly and concisely with others This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex,

ABOUT THE TEAM Integrity Data Science sits at the center of OpenAI’s mission to deploy powerful AI responsibly. We help ensure people can trust our products by building measurement systems, experimentation practices, and detection/mitigation strategies that protect OpenAI and our users from misuse, fraud, and evolving adversarial behaviors. As the scope and urgency of Integrity work expands across product surfaces and go-to-market motion, we’re hiring a dedicated Data Science Manager to scale the team, strengthen execution across multiple Integrity domains, and deepen partnership with Product, Engineering, Operations, and adjacent orgs (e.g., Growth, Ads). This role is based in our San Francisco HQ (in-office). ABOUT THE ROLE As Data Science Manager, Integrity, you will lead a team of data scientists working across trust & safety, fraud prevention, risk analysis, measurement, and modeling. You’ll be accountable for building a high-performing DS function that can keep pace with fast-moving threats—and for shaping the analytical strategy that informs how OpenAI detects, measures, and mitigates integrity risks at scale. This is a highly cross-functional leadership role. You’ll help set the roadmap with Integrity Product/Engineering leaders, evolve team structure and operating rhythms, raise the bar on technical rigor (experimentation, causal inference, modeling, metrics), and develop a culture of proactive, high-leverage impact. Many of the challenges in this space are emergent—new misuse patterns appear as the technology and ecosystem evolves—so this role requires strong judgment, comfort with ambiguity, and an ability to build systems that scale. IN THIS ROLE, YOU WILL: - Lead and scale a high-impact Integrity Data Science team—hiring, coaching, and developing DS ICs (and potentially future managers) while setting a strong technical and cultural bar. - Drive strategy across multiple Integrity domains (policy enforcement, bot detection, fraud prevention, IP theft, risk measurement, abuse prevention), balancing near-term response with durable systems. - Build and institutionalize analytical rigor: clear metric frameworks, experimentation standards, monitoring/alerting, and repeatable evaluation approaches for Integrity interventions. - Partner deeply with Product & Engineering to shape roadmaps, prioritize the right bets, and translate ambiguous risk signals into practical product and platform decisions. - Evolve team structure and operating model as the org scales—defining ownership boundaries, improving processes, and creating leverage through better tooling and AI-assisted workflows. - Enable cross-org outcomes, supporting partners outside Integrity (e.g., Growth, Ads, GTM) where integrity risks intersect with product and business goals. - Communicate clearly with senior leadership, synthesizing complex tradeoffs, surfacing risk, and driving alignment on priorities and success metrics. - Push the team toward an AI-leveraged operating mode, using modern tooling and model capabilities to accelerate detection, triage, analysis, and iteration. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have deep experience leading and scaling Data Science teams, ideally in trust & safety, fraud/abuse, security, risk, or other adversarial problem spaces in fast-moving environments. - Bring strong technical grounding across modern DS techniques (experimentation, causal inference, anomaly detection, risk modeling, measurement design) and can coach others to execute with rigor. - Have a track record of building durable partnerships across DS, Engineering, Product, and Operations—able to influence without authority and create shared accountability. - Are excellent at hiring, mentoring, and developing technical talent, and can build a culture that is both high-bar and supportive. - Can translate messy, evolving threats into clear frameworks, metrics, and decisions—and keep the team focused on the highest-leverage work. - Are comfortable operating in ambigu

ABOUT THE TEAM The Safety Systems team https://openai.com/safety/safety-systems is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Safety Research team aims to fundamentally advance our capabilities for precisely implementing robust, safe behavior in AI models, and to leverage these advances to make OpenAI’s deployed models safe and beneficial. This requires a breadth of new ML research to address the growing set of safety challenges as AI becomes more powerful and used in more settings. Key focus areas include how to enforce nuanced safety policies without trading off helpfulness and capabilities, how to make the model robust to adversaries, how to address privacy and security risks, and how to make the model trustworthy in safety-critical domains. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. ABOUT THE ROLE OpenAI is seeking a senior researcher with passion for AI safety and experience in safety research. Your role will set directions for research to enable and empower safe AGI and work on research projects to make our AI systems safer, more aligned and more robust to adversarial or malicious use cases. You will play a critical role in shaping how a safe AI system should look like in the future at OpenAI, making a significant impact on our mission to build and deploy safe AGI. IN THIS ROLE, YOU WILL: - Conduct state-of-the-art research on AI safety topics such as RLHF, adversarial training, robustness, and more. - Implement new methods in OpenAI’s core model training and launch safety improvements in OpenAI’s products. - Set the research directions and strategies to make our AI systems safer, more aligned and more robust. - Coordinate and collaborate with cross-functional teams, including T&S, legal, policy and other research teams, to ensure that our products meet the highest safety standards. - Actively evaluate and understand the safety of our models and systems, identifying areas of risk and proposing mitigation strategies. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Are excited about OpenAI’s mission https://openai.com/mission/ of building safe, universally beneficial AGI and are aligned with OpenAI’s charter https://openai.com/charter/ - Demonstrate a passion for AI safety and making cutting-edge AI models safer for real-world use. - Bring 4+ years of experience in the field of AI safety, especially in areas like RLHF, adversarial training, robustness, fairness & biases. - Hold a Ph.D. or other degree in computer science, machine learning, or a related field. - Possess experience in safety work for AI model deployment - Have an in-depth understanding of deep learning research and/or strong engineering skills. - Are a team player who enjoys collaborative work environments. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-

About the Team The Safety Systems https://openai.com/safety-systems/ team is dedicated to ensuring the safety, robustness, and reliability of AI models towards their deployment in the real world. OpenAI’s charter https://openai.com/charter/ calls on us to ensure the benefits of AI are distributed widely. Our Health AI team is focused on enabling universal access to high-quality medical information. We work at the intersection of AI safety research and healthcare applications, aiming to create trustworthy AI models that can assist medical professionals and improve patient outcomes. About the Role We’re seeking strong researchers who are passionate about advancing AI safety and improving global health outcomes. As a Research Scientist, you will contribute to the development of safe and effective AI models for healthcare applications. You will implement practical and general methods to improve the behavior, knowledge, and reasoning of our models in these settings. This will require research into safety and alignment techniques that we aim to generalize towards safe and beneficial AGI. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design and apply practical and scalable methods to improve safety and reliability of our models, including RLHF, automated red teaming, scalable oversight, etc. - Evaluate methods using health-related data, ensuring models provide accurate, reliable, and trustworthy information. - Build reusable libraries for applying general alignment techniques to our models. - Proactively understand the safety of our models and systems, identifying areas of risk. - Work with cross-team stakeholders to integrate methods in core model training and launch safety improvements in OpenAI’s products. You might thrive in this role if you: - Are excited about OpenAI’s mission of ensuring AGI is universally beneficial and are aligned with OpenAI’s charter. - Demonstrate passion for AI safety and improving global health outcomes. - Have 4+ years of experience with deep learning research and LLMs, especially practical alignment topics such as RLHF, automated red teaming, scalable oversight, etc. - Hold a Ph.D. or other degree in computer science, AI, machine learning, or a related field. - Stay goal-oriented instead of method-oriented, and are not afraid of unglamorous but high-value work when needed. - Possess experience making practical model improvements for AI model deployment. - Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. - Are a team player who enjoys collaborative work environments. - Bonus: possess experience in health-related AI research or deployments. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Ch

About the Team The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI. TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission. About the Role We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale. In this role, you will: - Design eval pipelines that are reliable, reproducible, and extendable - Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation - Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems - Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. - Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows - Own the full development lifecycle of new backend systems and internal platform capabilities - Build with scale and maintainability in mind, while rapidly iterating on new ideas You might be a great fit if you have: - 4+ years of backend engineering experience at product-driven companies (excluding internships) - Proficiency in backend technologies. Our tech stack includes Python, FastAPI, and Postgres - Experience designing and scaling distributed systems, APIs, or data processing pipelines - Have experience building AI agents or applications, including designing evals and improving performance through prompting or scaffolding - Are familiar with evaluation methods for LLMs and have worked with patterns like multi-agent workflows, tool use, or long context. - Experience creating production evals and/or measuring performance of ML/LLM models at scale - A pragmatic mindset. You’re comfortable shipping iteratively while building toward a long-term vision About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordan

About the Team The Alignment team at OpenAI is dedicated to ensuring that our AI systems are safe, trustworthy, and consistently aligned with human values, even as they scale in complexity and capability. Our work is at the cutting edge of AI research, focusing on developing methodologies that enable AI to robustly follow human intent across a wide range of scenarios, including those that are adversarial or high-stakes. We concentrate on the most pressing challenges, ensuring our work addresses areas where AI could have the most significant consequences. By focusing on risks that we can quantify and where our efforts can make a tangible difference, we aim to ensure that our models are ready for the complex, real-world environments in which they will be deployed. The two pillars of our approach are: (1) harnessing improved capabilities into alignment, making sure that our alignment techniques improve, rather than break, as capabilities grow, and (2) centering humans by developing mechanisms and interfaces that enable humans to both express their intent and to effectively supervise and control AIs, even in highly complex situations. About the Role As a Research Engineer / Research Scientist on the Alignment team, you will be at the forefront of ensuring that our AI systems consistently follow human intent, even in complex and unpredictable scenarios. Your role will involve designing and implementing scalable solutions that ensure the alignment of AI as their capabilities grow and that integrate human oversight into AI decision-making. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: We are seeking research engineers and research scientists to help design and implement experiments for alignment research. Responsibilities may include: - Develop and evaluate alignment capabilities that are subjective, context-dependent, and hard to measure. - Design evaluations to reliably measure risks and alignment with human intent and values. - Build tools and evaluations to study and test model robustness in different situations. - Design experiments to understand laws for how alignment scales as a function of compute, data, lengths of context and action, as well as resources of adversaries. - Design and evaluate new Human-AI-interaction paradigms and scalable oversight methods that redefine how humans interact with, understand, and supervise our models. - Train model to be calibrated on correctness and risk. - Designing novel approaches for using AI in alignment research You might thrive in this role if you: - Are a team player – willing to do a variety of tasks that move the team forward. - Have a PhD or equivalent experience in research in computer science, computational science, data science, cognitive science, or similar fields. - Have strong engineering skills, particularly in designing and optimizing large-scale machine learning systems(e.g., PyTorch). - Have a deep understanding of the science behind alignment algorithms and techniques. - Can develop data visualization or data collection interfaces (e.g., TypeScript, Python). - Enjoy fast-paced, collaborative, and cutting-edge research environments. - Want to focus on developing AI models that are trustworthy, safe, and reliable, especially in high-stakes scenarios. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of

ABOUT THE TEAM The Safety Systems team https://openai.com/safety/safety-systems is responsible for various safety work to ensure our best models can be safely deployed to the real world to benefit the society and is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Pretraining Safety team’s goal is to build safer, more capable base models and enable earlier, more reliable safety evaluation during training. We aim to: 1. Develop upstream safety evaluations that to monitor how and when unsafe behaviors and goals emerge; 2. Create safer priors through targeted pretraining and mid-training interventions that make downstream alignment more effective and efficient 3. Design safe-by-design architectures that allow for more controllability of model capabilities In addition, we will conduct the foundational research necessary for understanding how behaviors emerge, generalize, and can be reliably measured throughout training. ABOUT THE ROLE The Pretraining Safety team is pioneering how safety is built into models before they reach post-training and deployment. In this role, you will work throughout the full stack of model development with a focus on pre-training: - Identify safety-relevant behaviors as they first emerge in base models - Evaluate and reduce risk without waiting for full-scale training runs - Design architectures and training setups that make safer behavior the default - Strengthen models by incorporating richer, earlier safety signals We collaborate across OpenAI’s safety ecosystem—from Safety Systems to Training—to ensure that safety foundations are robust, scalable, and grounded in real-world risks. IN THIS ROLE, YOU WILL: - Develop new techniques to predict, measure, and evaluate unsafe behavior in early-stage models - Design data curation strategies that improve pretraining priors and reduce downstream risk - Explore safe-by-design architectures and training configurations that improve controllability - Introduce novel safety-oriented loss functions, metrics, and evals into the pretraining stack - Work closely with cross-functional safety teams to unify pre- and post-training risk reduction YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have experience developing or scaling pretraining architectures (LLMs, diffusion models, multimodal models, etc.) - Are comfortable working with training infrastructure, data pipelines, and evaluation frameworks (e.g., Python, PyTorch/JAX, Apache Beam) - Enjoy hands-on research — designing, implementing, and iterating on experiments - Enjoy collaborating with diverse technical and cross-functional partners (e.g., policy, legal, training) - Are data-driven with strong statistical reasoning and rigor in experimental design - Value building clean, scalable research workflows and streamlining processes for yourself and others About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are looking for a systems-minded engineer to help advance our kernel development, performance engineering, and hardware-software co-design capabilities, with a particular focus on AI-assisted workflows and tooling. This person will work at the intersection of kernel optimization, developer tooling, observability, and research infrastructure, helping us improve both how production kernels are built and optimized, and how future hardware-software systems are designed and evaluated. The role is ideal for someone who is excited by low-level performance work, but also sees AI and automation as powerful tools for accelerating engineering velocity. You will help define the future of kernel engineering in the era of AI-assisted development. In this role, you may: - Build developer tooling and workflows that make kernel development and performance optimization faster, more scalable, and easier to debug, integrate, and deploy. - Develop observability, diagnostics, and validation infrastructure that makes AI-assisted optimization systems more interpretable, reliable, and effective. - Optimize production kernels end to end by formulating optimization problems, running search loops, analyzing bottlenecks, debugging generated implementations, and landing improvements into production. - Design abstractions, interfaces, and automation systems that accelerate kernel optimization, correctness validation, and hardware-software co-design. - Improve AI-assisted optimization systems for specialized tasks through better datasets, evaluations, benchmarking, and research infrastructure. - Partner across research and engineering teams to turn new ideas into practical systems spanning production needs and long-term infrastructure strategy. You might thrive in this role if you have: - Strong systems or tooling engineering experience, with a background in low-level software, performance optimization, or infrastructure. - Experience with developer tooling, debugging infrastructure, profiling, observability, or workflow design for technical users. - Depth in kernel development, accelerator architecture, compiler systems, or related performance-critical domains. - Familiarity with AI-assisted systems, agentic workflows, post-training, or reinforcement learning for engineering or research applications. - Strong experimental judgment, comfort with ambiguity, and the ability to move fluidly between research exploration and production execution. - Interest in compilers, DSLs, program synthesis, or AI for systems. Preferred profile The ideal candidate is a strong systems and tooling engineer with real depth in kernels and accelerators. They are comfortable working across software and hardware boundaries, can reason deeply about performance, abstractions, and system design, and have hands-on experience optimizing code for GPUs, high-performance CPUs, or custom accelerators. They view AI not as the end product, but as a force multiplier for engineering productivity and system optimization. To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powe

About the Team The RL and Reasoning team drives the core reasoning paradigm and has created groundbreaking innovations such as o1 and o3. They focus on pushing the boundaries of reinforcement learning research, building next-generation generative models, and deploying them at scale. About the Role As a Research Engineer/Research Scientist at OpenAI, you will advance the frontier of AI alignment and capabilities through cutting-edge RL methods. Your work will sit at the heart of training intelligent, aligned, and general-purpose agents, including the systems that power various models. We’re looking for people who have a background in reinforcement learning research, are able to iterate quickly, and are proficient at coding. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if: - You love being on the cutting edge of RL and language model research. - You’re a self-starter who takes initiative and ownership of ideas, driving them to completion. - You value principled approaches, simple experiments in tightly-controlled settings, and reaching trustworthy conclusions which stand the test of time. - You thrive in a fast-paced, dynamic, and technically complex environment where rapid iteration is key. - You’re comfortable diving into a large ML codebase to debug and improve it. - You have a deep understanding of machine learning and machine learning applications. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link https://form.asana.com/?k=bQ7w9h3iexRlicUdWRiwvg&d=57018692298241. OpenAI Global

ABOUT THE TEAM The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. ABOUT THE ROLE As a member of Agent Post-Training, Computer Use, you will teach models to operate computers. You will help train models that can navigate browsers and desktops, use tools and applications, reason through complex workflows, collaborate with users and other agents, and complete long-horizon tasks with reliability and judgment. This work sits at the intersection of frontier model training, product behavior, evaluation, and systems engineering, and will directly shape the computer-use capabilities shipped in OpenAI’s next generation of agents. Currently, our models are the best in the world at this behavior! You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. IN THIS ROLE, YOU MIGHT - Design and run experiments that improve agentic model behavior for complex computer use https://openai.com/index/codex-for-almost-everything/, including desktop and browser. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. - Care about product impact and model behavior, n

ABOUT THE TEAM The Technical Success team is responsible for helping OpenAI’s customers realize meaningful and sustained value from our technology. We partner closely with customers throughout their deployment journey, helping them move from initial exploration to production applications and broader organizational adoption. The Enterprise AI Deployment Engineering team supports complex organizations across Professional Services, Media and Entertainment, Telecommunications, and Private Equity. These customers operate in varied environments—from global consulting and legal organizations to consumer media platforms, telecommunications providers, and private equity portfolios—but share a need to deploy AI securely, reliably, and at scale. AI Deployment Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They bring deep technical judgment, strong customer instincts, and the ability to translate frontier model capabilities into durable business outcomes. ABOUT THE ROLE We are seeking a Manager to build, lead, and develop a team of AI Deployment Engineers supporting OpenAI’s Enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful deployments across business units and workflows. This role requires a combination of technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and partnering with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how OpenAI serves enterprise customers at scale. This includes developing account coverage models, reusable deployment patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product signal. IN THIS ROLE, YOU WILL - Build, manage, and develop a high-performing team of AI Deployment Engineers supporting enterprise customers across Professional Services, Media and Entertainment, Telecommunications, and Private Equity. - Own the quality and impact of the team’s work across solution design, implementation, production readiness, adoption, and expansion. - Coach the team through complex decisions involving architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost. - Establish a clear operating model for prioritizing accounts and engagements based on customer need, strategic value, technical complexity, and the potential for repeatable impact. - Serve as a senior technical escalation point during critical launches, production incidents, complex integrations, and high-stakes customer decisions. - Partner with customer executives and technical leaders to connect deployment decisions to measurable business and operational outcomes. - Help customers progress from isolated experimentation to production deployments and sustained adoption across teams, workflows, and business units. - Work closely with Sales and Solutions Engineering to create continuity across the customer lifecycle and maintain shared accountability for customer success. - Translate customer needs and recurring deployment challenges into actionable feedback for Product, Research, Engineering, Security, and other internal teams. - Distinguish scalable market patterns from bespoke requests and advocate for investments that can benefit multiple customers. - Develop reusable architectures, evaluation approaches, playbooks, tooling, and enablement that improve time to value across the enterprise portfolio. - Create mechanisms to measure production deployments, usage, a

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role We are looking for engineers to operate the next generation of compute clusters that power OpenAI’s frontier research. This role blends distributed systems engineering with hands-on infrastructure work on our largest datacenters. You will scale Kubernetes clusters to massive scale, automate bare-metal bring-up, and build the software layer that hides the complexity of a magnitude of nodes across multiple data centers. You will work at the intersection of hardware and software, where speed and reliability are critical. Expect to manage fast-moving operations, quickly diagnose and fix issues when things are on fire, and continuously raise the bar for automation and uptime. In this role, you will: - Spin up and scale large Kubernetes clusters, including automation for provisioning, bootstrapping, and cluster lifecycle management - Build software abstractions that unify multiple clusters and present a seamless interface to training workloads - Own node bring-up from bare metal through firmware upgrades, ensuring fast, repeatable deployment at massive scale - Improve operational metrics such as reducing cluster restart times (e.g., from hours to minutes) and accelerating firmware or OS upgrade cycles - Integrate networking and hardware health systems to deliver end-to-end reliability across servers, switches, and data center infrastructure - Develop monitoring and observability systems to detect issues early and keep clusters stable under extreme load You might thrive in this role if you: - Have deep experience operating or scaling Kubernetes clusters or similar container orchestration systems in high-growth or hyperscale environments - Bring strong programming or scripting skills (Python, Go, or similar) and familiarity with Infrastructure-as-Code tools such as Terraform or CloudFormation - Are comfortable with bare-metal Linux environments, GPU hardware, and large-scale networking - Enjoy solving fast-moving, high-impact operational problems and building automation to eliminate manual work - Can balance careful engineering with the urgency of keeping mission-critical systems running Qualifications - Experience as an infrastructure, systems, or distributed systems engineer in large-scale or high-availability environments - Strong knowledge of Kubernetes internals, cluster scaling patterns, and containerized workloads - Proficiency in cloud infrastructure concepts (compute, networking, storage, security) and in automating cluster or data center operations Bonus: background with GPU workloads, firmware management, or high-performance computing About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies

About the role We’re looking for an engineering manager to lead a team building software systems that detect and prevent harmful misuse of frontier AI models—before incidents occur. This is a builder’s role: you’ll lead engineers shipping production services, detection pipelines, and mitigation mechanisms that protect frontier model integrity and reduce high-severity misuse risk. While this work intersects with frontier model development, security and risk, we’re explicitly seeking someone with a software engineering foundation who is comfortable building reliable systems that can operate at billions of users scale. In this role you will: - Lead a team of software engineers building detection + mitigation systems for frontier model misuse, with an emphasis on model IP protection / distillation detection and emerging risk surfaces from autonomous agents. - Set the technical roadmap and execution strategy: prioritize, design, ship, iterate, measure impact. - Build production systems: services, pipelines, tooling, instrumentation, and automation that scale with frontier model usage. - Partner deeply with Research and Product to translate evolving model capabilities into concrete tests, signals, and mitigations that can be deployed at scale. - Drive strong engineering fundamentals: architecture, reliability, monitoring, performance, and operational excellence. - Hire and grow an exceptional team across backend, data systems, and applied ML engineering domains as needed. - Anticipate what breaks at scale as agentic workflows become more capable. You might thrive in this role if you: - Experience building systems in adversarial, fast-evolving environments - Are comfortable with ambiguity and novelty - Have experience adjacent to security (e.g., abuse prevention, fraud, integrity, platform defense, auth/identity, malware/spam, adversarial environments) - Communicate clearly and build trust quickly with senior stakeholders—pragmatic, collaborative, and calm under scrutiny. - Significant experience leading engineering teams and delivering production systems end-to-end. - Strong technical judgment in system design, distributed systems, data pipelines, observability, and operational reliability. - Demonstrated ability to partner cross-functionally with Research/Product/Security to ship systems that materially reduce risk or abuse at scale. - Familiarity with model extraction / distillation, adversarial evaluation, or scalable detection/mitigation approaches. - Background in autonomy, high-scale real-time systems, or intelligence-adjacent technical domains is a plus. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably

About the Team With Codex we’re building an AI software engineer. One that you can pair with, delegate to, or even ask to take on future tasks proactively. Our team is a fast-moving group within OpenAI, bringing together research, engineering, design, and product. We iteratively build the Codex agent harness and product to get the most out of the model, and we iteratively train the model to be great at complex software engineering tasks. The Codex team is responsible for building state-of-the-art AI systems that can write code, reason about software, and act as intelligent agents for developers and non-developers alike. We operate across research, engineering, product, and infrastructure; owning the full lifecycle of experimentation, deployment, and iteration on novel coding capabilities. Codex Enterprise builds the ecosystem building blocks, discovery surfaces, and enterprise capabilities that help Codex spread across developers, teams, and organizations worldwide. It is a cross-cutting team that works across the stack to build both delightful product experiences and fundamental platform capabilities. Its customers range from individual developers and small teams to large enterprises, and our mission is critical to achieving the vision of Codex as a proactive teammate. About the Role As we grow, we’re focused on turning Codex from a powerful individual tool into a production-grade teammate for entire organizations. You will work across internal OpenAI teams and external customers, from fast-moving startups to large enterprises, to make it possible to deploy, operate, and trust Codex in increasingly demanding real-world environments. As Codex’s consumer adoption accelerates, enterprise demand is growing just as quickly, and there is also increasing opportunity to expand Codex through ecosystem capabilities that unlock new workflows, integrations, and discovery. This team helps turn messy, real-world team requirements into robust, repeatable, and scalable product and platform capabilities. You will work directly with a small set of deeply engaged design-partner customers using their real deployments to surface opportunities, and what’s required for Codex to succeed inside modern engineering organizations. Those insights will drive what you build across product, infrastructure, deployment patterns, and ecosystem capabilities for all teams using Codex. This role owns systems end-to-end: from architecture and implementation to production operations with a strong bias for both quality and velocity. In this role, you will: - Shape the evolution of Codex by identifying how teams actually use (and break) AI-powered software engineering, and driving changes across product, infrastructure, ecosystem surfaces, and model behavior to make Codex a truly reliable teammate for organizations. - Build the core ecosystem, team, and enterprise primitives that make Codex usable at scale, including plugins, skills, hooks, discovery surfaces, RBAC, admin and audit surfaces, usage, rate limits and pricing controls, managed configuration and constraints, and analytics that give teams and operators deep visibility into how Codex is being used. - Design and own secure, observable, full-stack systems that power Codex across web, IDEs, CLI, and CI/CD, integrating with enterprise identity and governance systems (SSO/SAML/OIDC, SCIM, policy enforcement) and building data-access patterns that are performant, compliant, and trustworthy. - Lead real-world deployments and launches by working directly with customers and the Go To Market team (GTM) to roll Codex out across teams, using live usage and operational signals to rapidly iterate and turn messy, real-world feedback into scalable product, platform, and ecosystem improvements. You might thrive in this role if you: - Have strong software engineering fundamentals and experience turning ideas into productionized systems, thinking holistically about speed, performance, and user experience. - Are proficient in

About the Team The Human Data team turns human feedback into reliable signals for training and evaluation. We design and run end-to-end programs that capture the depth of human intent behind everyday and high-stakes uses of our models. Our remit spans bespoke data campaigns, scalable synthetic data generation, and product-embedded signals. We partner closely across all research teams to translate these signals into training datasets, novel evaluations, and feedback loops that push the frontier of our models and advance their applications. About the Role As a Program Manager (PGM) in the Human Data team you will partner with our research teams, operations and engineering to execute complex programs for collecting high-quality data. You will be a key interface between our external vendors and AI trainers, ensuring human data campaigns are successfully completed. Your work will play a key role in enabling OpenAI to train safe models that will land in the real world This role is based in our San Francisco HQ. In this role, you will: - Work in a high velocity environment, where the outcome of your work will have a direct impact on the models that OpenAI deploy in the real world - Work closely with external vendors, trainers and internal researchers to collect, review, and deliver high-quality data - Gather requirements, write instructions, define success criteria, and calibrate the AI trainers - Use internal tooling to assess labeled data and provide feedback to AI trainers - Think critically and share recommendations on tooling and process improvements, optimizing for quality, throughput, and AI trainer experience You’ll thrive in this role if: - You thrive in dynamic environments. You are comfortable navigating ambiguity, managing shifting priorities, and adapting to fast-paced changes without missing a beat. - You’re curious about AI, LLMs, Agents. While not required, an interest or background in these areas will help you connect the dots in our broader mission. - You have a can-do attitude. You don’t shy away from rolling up your sleeves and tackling the "grunt work" with the same enthusiasm as high-visibility tasks. - You’re an excellent communicator. You love bringing people together, fostering collaboration, and providing clarity in complex situations. Your empathetic approach helps you understand different perspectives and build strong, trusting relationships. - You are resilient and flexible. Setbacks don’t rattle you. You bounce back quickly, adjust strategies as needed, and maintain a positive, solution-oriented mindset. - You’re super organized amidst chaos. Even when things are moving quickly, you keep track of details, manage competing demands, and bring structure to complexity. - You enjoy operational work. While you might have an interest in broader topics like safety, you find satisfaction in executing operational tasks efficiently and effectively. - You have a knack for data. You've gone beyond basic data annotation and have hands-on experience with data analytics, using insights to inform decisions and improve processes. - You’re energized by start-up environments. If you enjoy the hustle, resourcefulness, and rapid iteration typical of start-ups, you’ll feel right at home. - You have some relevant experience. Ideally, you have at least 1-2 years of relevant experience and are eager to grow within a role that challenges and develops your skills. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not

ABOUT THE TEAM Security is at the foundation of OpenAI’s mission to ensure that artificial general intelligence benefits all of humanity. The Security team protects OpenAI’s technology, people, and products. We are technical in what we build but are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. ABOUT THE ROLE We’re seeking an exceptional Staff - Principal level offensive security domain expert to build agents that continuously identify and coordinate remediation of vulnerabilities across OpenAI’s infrastructure and applications. You will be the technical owner of this effort, combining deep offensive security judgment with agent engineering to build a production system that can operate safely and reliably at scale. As OpenAI increasingly uses automation throughout the company, we believe our security testing must become increasingly automated as well. Advances in model capabilities create an opportunity to test more of our attack surface than would be possible through human effort alone and a need to ensure that we remain ahead of those same capabilities as they become available to attackers. In this role, you’ll build a portfolio of specialized agents that develop a deep understanding of OpenAI’s infrastructure, applications, processes, and security boundaries. These agents will combine internal context with feedback from running systems to explore our cloud environments, Kubernetes clusters, web applications, endpoints, external attack surface, and other high-value targets. The goal is for agents to not only discover vulnerabilities, but also to validate exploitability, document impact, drive remediation, and verify fixes. Success will be measured through outcomes like vulnerabilities fixed, attack surface covered, and performance on evals you’ll build. These systems will operate continuously and with increasing autonomy, while using carefully designed guardrails and human-in-the-loop controls for dangerous actions. They will also learn from feedback from other domain experts throughout the company. IN THIS ROLE, YOU WILL: - Serve as the technical owner of OpenAI’s offensive security agents, establishing its architecture, technical direction, operating model, and evaluation strategy. - Design and build a portfolio of specialized agents that continuously test OpenAI’s infrastructure and applications from a variety of authenticated and unauthenticated perspectives. - Translate expert offensive security workflows and intuition into tools, skills, harnesses, policies, and internal knowledge bases. - Build agents that deeply understand OpenAI’s environment by integrating internal context. - Develop capabilities for testing cloud and Kubernetes environments, modern web applications, external attack surface, endpoints, and other high-value systems. - Build complete vulnerability-management loops that move beyond discovery to impact validation, ownership identification, prioritization, remediation support, progress tracking, and fix verification. - Design human-in-the-loop systems that allow offensive security engineers to approve or reject potentially dangerous actions, provide missing context, redirect investigations, and steer agents away from unproductive paths. - Create feedback mechanisms that allow agents to learn from the decisions, corrections, and domain expertise of experienced offensive security practitioners. - Develop rigorous evaluations that measure meaningful security outcomes and improvements in agent capability over time. - Build production-quality infrastructure that allows the system to run continuously, recover from failures, remain observable and debuggable, and operate safely against production systems. - Investigate failures in agent reasoning and behavior, identify where models are

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: 1. Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. 2. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. 3. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework https://openai.com/index/updating-our-preparedness-framework/, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE We are looking to hire exceptional research engineers that can push the boundaries of our frontier models. Specifically, we are looking for those that will help us shape our empirical grasp of the whole spectrum of AI safety concerns and will own individual threads within this endeavor end-to-end. You will own the scientific validity of our frontier preparedness capability evaluations—designing new evals grounded in real threat models (including high-consequence domains like CBRN as well as cyber and other frontier-risk areas), and maintaining existing evals so they don’t stale or silently regress. You’ll define datasets, graders, rubrics, and threshold guidance, and produce auditable artifacts (evaluation cards, capability reports, system-card inputs) that leadership can trust during high-stakes launches. IN THIS ROLE, YOU'LL: - Work on identifying emerging AI safety risks and new methodologies for exploring the impact of these risks - Build (and then continuously refine) evaluations of frontier AI models that assess the extent of identified risks - Design and build scalable systems and processes that can support these kinds of evaluations - Contribute to the refinement of risk management and the overall development of "best practice" guidelines for AI safety evaluations YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Are passionate and knowledgeable about short-term and long-term AI safety risks - Demonstrate the ability to think outside the box and have a robust “red-teaming mindset” - Have experience in ML research engineering, ML observability and monitoring, creating large language model-enabled applications, and/or another technical domain applicable to AI risk - Are able to operate effectively in a dynamic and extremely fast-paced research environment as well as scope and deliver projects end-to-end IT WOULD BE GREAT IF YOU ALSO HAVE: - First-hand experience in red-teaming systems—be it computer systems or otherwise - A good understanding of the (nuances of) societal aspects of AI deployment - Excellent communication skills and the ability to work cross-functionally This role may require access to technology or technical data controlled under the U.S. Export Administration Regulations or International Traffic in Arms Regulations. Therefore, this role is restricted to individuals described in paragraph (a)(1) of the definition of “U.S. person” in the U.S. Export Administration Regulations, 15 C.F.R. § 772.1, and in the International Traffic in Arms Regulations, 22 C.F.R. § 120.62. U.S. persons are U.S. citizens, U.S. legal permanent residents, individuals granted asylum status in the United States, and individuals admitted to the United States as refugees. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different pers

About the Team The Privacy Team at OpenAI is committed to building a secure and trustworthy platform. Our area of responsibility encompasses all OpenAI products and systems that process user data. We provide cross-functional partners with the tools needed to ensure that all products adhere to the highest standards of data privacy and legal compliance. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing Artificial General Intelligence (AGI) that offers widespread benefits. About the Role We’re in search of a Software Engineer with experience building data pipelines and working closely with members of the Legal team. This role is perfect for someone who's passionate about the intersection of systems, privacy, and legal compliance. You will architect, design, and write backend systems responsible for handling some of the most sensitive data at OpenAI. This role is based in Dublin, Ireland. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, build, and maintain back-end systems and services that power privacy and data compliance functions within our API products and consumer applications. - Work closely with legal advisors and other engineers to respond to court orders and other legal processes, all while upholding strict data privacy and legal standards. - Identify opportunities for automation and build the tools that enable other teams to automate tasks involving customer data. - Develop and implement data handling policies and procedures in compliance with legal and ethical standards, ensuring the integrity and confidentiality of user data. You might thrive in this role if you: - Have experience building data pipelines, especially for legal processes and investigative workflows. - Can translate legal requirements into technical solutions and explain technical solutions to a non-technical audience. - Take responsibility for problems from beginning to end, and are prepared to acquire any missing knowledge necessary to get the job done. - Create tools to speed up your own and your colleagues’ workflows, particularly when pre-existing solutions are inadequate. - Deeply care about user experience and take pride in developing products that meet customer needs while ensuring privacy. - Have a background in security investigations or experience working in collaboration with trust and safety, legal, and engineering teams. Compensation, Benefits and Perks This is a position with OpenAI Ireland Ltd., which controls the hiring and management of this position. Total compensation includes an annual salary, generous equity, and benefits. - Medical, dental, and vision insurance for you and your family - Mental health and wellness support - PRSA plan with 6% employer matching - Unlimited time off - Annual learning & development stipend (€1,400 per year) About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants w

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training Performance Engineer, you’ll drive efficiency improvements across our distributed training stack. You’ll analyze large-scale training runs, identify utilization gaps, and design optimizations that push the boundaries of throughput and uptime. This role blends deep systems understanding with practical performance engineering — analyzing GPU kernel performance, collective communication throughput, investigating I/O bottlenecks, and sharding our models so we can train them at massive scale. You’ll help ensure that our clusters are running at peak performance, enabling OpenAI to train larger, more capable models with the same compute budget. This role is based in San Francisco, CA. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. In this role, you will: - Profile end-to-end training runs to identify performance bottlenecks across compute, communication, and storage. - Optimize GPU utilization and throughput for large-scale distributed model training. - Collaborate with runtime and systems engineers to improve kernel efficiency, scheduling, and collective communication performance. - Implement model graph transforms to improve end to end throughput. - Build tooling to monitor and visualize MFU, throughput, and uptime across clusters. - Partner with researchers to ensure new model architectures scale efficiently during pre-training. - Contribute to infrastructure decisions that improve reliability and efficiency of large training jobs. You might thrive in this role if you: - Love optimizing performance and digging into systems to understand how every layer interacts. - Have strong programming skills in Python and C++ (Rust or CUDA a plus). - Have experience running distributed training jobs on multi-GPU systems or HPC clusters. - Enjoy debugging complex distributed systems and measuring efficiency rigorously. - Have exposure to frameworks like PyTorch, JAX, or TensorFlow and an understanding of how large-scale training loops are built. - Are comfortable collaborating across teams and translating raw profiling data into practical engineering improvements. Nice to have: - Familiarity with NCCL, MPI, or UCX communication libraries. - Experience with large-scale data loading and checkpointing systems. - Prior work on training runtime, distributed scheduling, or ML compiler optimization. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different p

About the Team Our Safety Systems https://openai.com/safety/safety-systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. Within Safety Systems, the Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. About the Role Frontier AI systems are rapidly expanding what is possible in cybersecurity and software engineering. These capabilities create major defensive opportunities, but they also raise serious dual-use and misuse risks across areas such as malware development, exploit discovery, vulnerability chaining, credential abuse, cyber intrusion, and autonomous offensive operations. In this role, you will help define how OpenAI’s models should behave in high-risk cybersecurity contexts. You will develop policy frameworks, threat models, taxonomies, evaluations, and behavioral specifications that guide model behavior across training, deployment, and monitoring systems. This role sits at the intersection of cybersecurity, AI safety, threat modeling, evaluation science, and policy implementation. You will work closely with research, engineering, safety training, preparedness, and product teams to build policies that are technically grounded, measurable, enforceable, and responsive to real-world cyber risk. Your Responsibilities: - Design and maintain model policies for cybersecurity and frontier-risk domains, especially dual-use and high-risk cyber capabilities. - Translate cybersecurity threat models into clear behavioral specifications, evaluation criteria, grading guidance, and system-level mitigations. - Define practical boundaries between legitimate security research, defensive workflows, and assistance that could materially enable harmful activity. - Build policy artifacts that support implementation across training, evaluation, deployment, monitoring, and escalation systems. - Partner with safety researchers, engineers, and evaluation teams to operationalize policies into scalable model behavior and measurable safeguards. - Analyze red-teaming results, deployment data, model failures, over-refusals, and ambiguous edge cases to improve policy and evaluation quality over time. - Identify emerging cyber capability areas where advanced AI systems could lower barriers to misuse or increase operational capability for malicious actors. - Contribute to system cards, safety reports, policy documentation, and external communications on OpenAI’s approach to cyber risk mitigation. We’re Seeking: - Strong technical expertise in cybersecurity, such as offensive security, defensive security, vulnerability research, malware analysis, incident response, threat intelligence, application security, exploit development, infrastructure security, or cloud security. - Strong judgment about how AI systems may affect the cyber threat landscape, including dual-use, autonomous, or agentic system risks. - Ability to distinguish between legitimate security use cases and assistance that could materially enable harmful cyber activity. - Experience building or applying threat models to complex technical systems, especially in adversarial or high-risk environments. - Ability to translate technical security expertise into structured policy frameworks, evaluation criteria, operational guidance, and enforcement mechanisms. - Comfort using empirical evidence, including evaluations, red-teaming results, deployment observations, and model failure modes, to inform policy decisions. - Strong systems thinking across policy, evaluations, classifiers, training, deployment safeguards, measurement, and monitoring. - Ability to work cross-functionally with researchers, engineers, product teams, policy experts, and operational stakeholders. - Stro

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: - Tracking and prediction. Monitoring https://openai.com/index/how-we-monitor-internal-coding-agents-misalignment/ and predicting the evolving misalignment propensities and capabilities of frontier AI systems. - Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. - Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE Preparedness is hiring strong technical executors to support preparations for recursive self-improvement. This work relies on reasoning about problems that might exist in the future, but might not exist now; so it’s especially important that people in this role are tasteful and strategic. The role is wide-ranging, covering any mitigation for loss of control risk, spanning the design and implementation of better pre-deployment risk-assessment https://alignment.openai.com/prod-evals/, control measures, RSI-relevant training interventions, and turning one’s technical work into established institutional practices. Below is a subset of our focus areas: - Scalable oversight: Establishing practices for model misbehavior monitoring and oversight which remain effective in superhuman model capability regimes, with a focus on bridging from today’s monitoring approaches to future-proof ones. - Automated auditing: As model capabilities increase, we’ll increasingly rely on automated approaches for finding the most severe forms of model misalignments. We’ll both need to sift through large swaths of production traffic https://openai.com/index/how-we-monitor-internal-coding-agents-misalignment/ to find the most egregious misalignments, and reliably elicit tail risks before deployment. - Rigorous monitorability: Rigorous testing and red-teaming of our measurements of model misbehavior related to loss-of-control (e.g. reward hacking, sandbagging, scheming). This includes better https://arxiv.org/abs/2603.05706 understanding https://alignment.openai.com/accidental-cot-grading/ monitorability https://arxiv.org/abs/2512.18311, and e.g. preparing for potential losses of Chain-of-Thought monitorability. - Model behavior science: Design experiments and evaluations to understand the extent to which models are problematically misaligned, or their safety-relevant capabilities lag behind dangerous capabilities. This may include training model organisms of misbehavior for behaviors not currently present in production, or training interventions to increase safety-relevant capabilities. - Coordination and verification: Prototype technical mechanisms for verifying compliance with potential future AI safety agreements. - AI R&D risk measurement: Track progress toward automation of technical staff to inform OpenAI’s near-term investments in alignment and security. - Maintaining and strengthening RSI safety cases: We’re especially interested in identifying and addressing blindspots of mitigation areas which we may have missed. Generally, our team alternates between performing rigorous hypothesis-driven research and turning our insights into interventions or control systems which impact production models, with occasional support of engineering teams. IN THIS ROLE, YOU WILL: - Carefully consider the problems OpenAI might face in the future and how to prepare for them. - Turn an open-ended objective like “prepare for future security threats” into a much more concrete direction (e.g. “implement monitors for data poisoning”) – prioritizing the work that is most useful to start right now. - Execute quickl

About the Team OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. About the Role As an Engineer on our hardware optimization and co-design team, you will co-design future hardware from different vendors for programmability and performance. You will work with our kernel, compiler and machine learning engineers to understand their unique needs related to ML techniques, algorithms, numerical approximations, programming expressivity, and compiler optimizations. You will evangelize these constraints with various vendors to develop and influence future hardware architectures towards efficient training and inference on our models. If you are excited about efficiently distributing a large language model across devices, dealing with and optimizing system-wide/rack-wide networking bottlenecks and eventually tailoring the compute pipe and memory hierarchy of the hardware platform, simulating workloads at different abstractions and working closely with our partners, this is the perfect opportunity! This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Key Responsibilities - Co-design future hardware for programmability and performance with our hardware vendors - Assist hardware vendors in developing optimal kernels and add support for it in our compiler - Develop performance estimates for critical kernels for different hardware configurations and drive decisions on compute core and memory hierarchy features - Build system performance models at different abstraction levels and carry out analysis to drive decisions on scale up, scale out, front end networking - Work with machine learning engineers, kernel engineers and compiler developers to understand their vision and needs from high performance accelerators - Manage communication and coordination with internal and external partners - Influence the roadmap of hardware partners to optimize them for OpenAI’s workloads. - Evaluate potential partners’ accelerators and platforms. - As the scope of the role and team grows, understand and influence roadmaps for hardware partners for our datacenter networks, racks, and buildings. Qualifications - 4+ years of industry experience, including experience harnessing compute at scale and optimizing ML platform code to run efficiently on target hardware. - Strong experience in software/hardware co-design - Deep understanding of GPU and/or other AI accelerators - Experience with CUDA, Triton or a related accelerator programming language - Experience driving Machine Learning accuracy with low precision formats - Experience with system performance modeling and analysis to optimize ML model deployment - Strong coding skills in C/C++ and Python - Are familiar with the fundamentals of deep learning computing and chip architecture/microarchitecture. - Able to actively collaborate with ML engineers, kernel writers, compiler developers, system engineers, chip architects/microarchitects Preferred Skills - PhD in Computer Science and Engineering with a specialization in Computer Architecture, Parallel Computing. Compilers or other Systems - Strong understanding of LLMs and challenges related to their training and inference About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world

About the Team OpenAI’s AI Deployment Engineering team helps organizations turn frontier AI capabilities into safe, reliable, and high-impact production systems. We work with customer executives, product and engineering teams, security leaders, and transformation teams to identify valuable opportunities, accelerate technical implementation, and scale what works. Enterprise deployments are defined by complexity rather than any one industry: existing architectures, diverse data environments, security and governance requirements, multiple stakeholder groups, and organization-wide change. We turn lessons from these deployments into better products and reusable patterns for customers everywhere. About the Role As an Enterprise AI Deployment Engineer, you will partner directly with leading organizations to design, build, and deploy AI systems that deliver measurable business outcomes. You will combine deep technical judgment, hands-on engineering, and customer leadership to take ambitious ideas from use-case selection and architecture through prototyping, evaluation, production launch, and scale. You will write and debug code, build evaluation systems, resolve complex integrations, and guide decisions involving model behavior, reliability, latency, cost, safety, security, governance, and operational readiness. Success is measured by production systems, sustained adoption, and meaningful customer impact—not simply activity or successful demonstrations. This is a rare opportunity to work on consequential real-world deployments at the frontier of AI while directly influencing how OpenAI’s products evolve. This role is based in our SF or NYC office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Partner directly with enterprise customers to identify high-value opportunities and translate them into technical architectures, implementation plans, evaluation strategies, and measurable success criteria. - Design, build, and deploy AI systems that solve important customer problems and produce measurable business outcomes. - Work hands-on in code to build prototypes, evaluation harnesses, reference implementations, integrations, and production accelerators. - Make sound technical decisions across models, agents, retrieval, tools, data, reliability, observability, latency, cost, safety, security, and governance. - Diagnose complex implementation challenges, reproduce failures, test hypotheses, and drive blockers toward resolution. - Help customers progress from promising prototypes to reliable production systems, sustained adoption, and scaled impact. - Partner closely with customer engineering teams and OpenAI Product, Research, Engineering, Security, and go-to-market teams, translating deployment experience into high-signal product feedback. - Create reusable architectures, tooling, playbooks, and technical guidance that accelerate future enterprise deployments. You’ll thrive in this role if you: - Have a demonstrated track record of designing, building, and delivering AI or machine-learning systems in enterprise environments, including taking systems from prototype to production. Relevant backgrounds may include applied AI or ML engineering, forward-deployed engineering, software engineering, customer engineering, solutions architecture, or technical consulting. - Can point to substantial personal contributions in code, architecture, evaluation, debugging, or production engineering—not only program or stakeholder management. - Are highly proficient in Python and comfortable working across an AI application stack; experience with JavaScript, TypeScript, or another relevant language is valuable. - Understand how to evaluate AI systems systematically using representative data, graders, production signals, and human judgment. - Have navigated enterprise production requirements such as integrations, reliability, observability, security, privacy, data governan

About the Team OpenAI is building AI systems that can help professionals perform complex, high-value work with greater speed, rigor, and creativity. Investment banking is one of the most demanding environments for knowledge work: bankers must synthesize fragmented information, exercise judgment under pressure, and produce precise, defensible models, analyses, and client materials. Our team works across Research, Product, Engineering, and Go-to-Market to make OpenAI's models genuinely useful for these workflows. We translate real professional work into product requirements, evaluations, training signals, and repeatable customer solutions. We care not only whether a model can generate an answer, but whether it can deliver accurate, defensible work that experienced bankers can trust and use. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. About the Role We are looking for a Subject Matter Expert in Investment Banking to help define what excellent AI-assisted banking work looks like and turn that standard into better models and products. You will bring deep, current knowledge of how investment banking work is actually performed, including company and industry research, financial analysis and modeling, valuation, diligence, transaction execution, and the creation and review of client materials. You will use that expertise to design realistic tasks and evaluations, create and assess high-quality reference work, diagnose model failures, and help our technical teams improve model behavior and product experiences. This is a hands-on individual-contributor role for someone who enjoys both doing the work and explaining what makes it good. You should be comfortable moving between an Excel model, a presentation, a source document, an evaluation rubric, a product prototype, and a conversation with researchers or customers. You will help us distinguish outputs that merely look plausible from work that is accurate, traceable, internally consistent, and ready for serious professional use. In This Role, You Will - Define the quality bar for AI-assisted investment banking work across research, financial analysis, valuation, modeling, diligence, transaction execution, and client materials. - Translate real banking workflows into challenging, representative evaluation tasks with realistic inputs, constraints, deliverables, and success criteria. - Create and refine banker-grade reference artifacts, including financial models, valuation analyses, diligence materials, screening outputs, pitch books, committee materials, and transaction documents. - Develop rigorous rubrics and grading methods that assess financial correctness, analytical judgment, source quality, traceability, internal consistency, presentation quality, and practical usefulness. - Evaluate model outputs and end-to-end agent workflows, identify recurring failure modes, and translate findings into actionable feedback for Research, Engineering, and Product. - Partner with researchers and engineers on evals, graders, datasets, human-review processes, tools, and product integrations that improve model performance on financial work. - Work closely with product teams to identify the highest-value opportunities for AI in investment banking, prototype new workflows using OpenAI tools, and assess whether early experiences meet the needs of real users. - Engage with customers, design partners, and domain reviewers to understand real-world standards and constraints, support testing and adoption, codify domain knowledge, and ensure responsible financial-services deployment. You Might Thrive in This Role If You - Have 2+ years of investment banking experience, including live transaction execution and the production of high-quality analyses, financial models, and client materials. Demonstrated ability and judgment matter more than title or tenure. - Have strong command of core banking workflows ac

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions designed for the unique demands of advanced AI workloads. We work closely with architecture, infrastructure, and vendor teams to evaluate system performance and guide critical design decisions. Our team focuses on building and applying performance modeling frameworks to understand system behavior, quantify tradeoffs, and inform next-generation infrastructure design. About the Role We are seeking Performance Modeling Engineers to develop and apply modeling tools that evaluate AI system performance and inform architectural decisions. In this role, you will work closely with the Performance Modeling Lead and partner teams to analyze system behavior, run simulations or analytical models, and help quantify tradeoffs across compute, memory, networking, and storage. You will contribute to building modeling frameworks and applying them to real-world questions that impact system design and vendor decisions. This role is well-suited for engineers with strong software or modeling backgrounds who are interested in developing deeper expertise in system architecture and AI infrastructure. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance. Key Responsibilities - Develop and maintain performance modeling tools and frameworks. - Build models to evaluate system behavior across: - compute, memory, and interconnect subsystems - distributed system scaling and bottlenecks. - Run simulations and analytical models to support architectural tradeoff analysis. - Collaborate with performance modeling lead and system architects to answer forward-looking design questions. - Analyze and interpret modeling outputs, translating results into actionable insights. - Validate models against real system measurements and workload behavior. - Contribute to improving modeling fidelity, usability, and scalability. Qualifications - Strong software engineering or modeling background (e.g., simulation, systems modeling, or performance analysis). - Familiarity with system architecture fundamentals (compute, memory, networking). - Experience with programming and building technical tools or frameworks. - Ability to reason about performance bottlenecks and scaling behavior. - Strong analytical skills and comfort working with quantitative models. - Ability to collaborate across teams and learn new system domains quickly. Preferred Skills - Exposure to AI/ML workloads or distributed systems. - Experience with simulation tools, performance modeling, or systems analysis. - Familiarity with data center infrastructure or large-scale systems. - Experience working with performance data, benchmarking, or profiling tools. - Interest in system architecture and hardware/software co-design. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent

About the Team The Personal AGI team seeks to empower all of humanity to benefit from frontier intelligence in whatever way they choose. We are responsible for training models to deploy to millions of users globally via ChatGPT, the API, and future products. We aim to evolve ChatGPT from a chatbot to an infinitely capable and personalized superassistant supporting human flourishing. We work on defining, measuring, and improving capabilities across the training stack. Our focus areas include but are not limited to model behavior, personalization, safety, factuality, instruction following, personality, interactivity, multilingual fluency, world interaction, and bringing agents to everyone. We chart the course for what to strive towards. We partner closely with research and product teams across the company ensuring that our models are safe, efficient, and reliable. About the Role You’ll work as a Research Engineer / Scientist on the North Stars team within the broader Personal AGI research org. You will work on bringing the next generation of AI-enabled experiences to all of humanity by closing the capability overhang between power users and the average consumer, including areas like tool-use, feature discovery, connectors, and instruction following. You will think deeply about the current bottlenecks in model behavior, translate these insights into robust evals, training data, reward signals, and model and harness improvements. We're looking for individuals with strong ML engineering skills and research experience passionate about creative, product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own and pursue a research agenda to improve model capability and performance. - Collaborate closely with the other research and product teams, allowing customers to optimize their own models. - Build robust evaluations for tracking modeling improvements. - Design, implement, test, and debug code across our research stack. You might thrive in this role if you: - Have a deep understanding of machine learning and machine learning applications. - Have a working knowledge of relevant models, and building evaluations for model capability improvement. - Are comfortable diving into a large ML codebase to debug. - Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a condit

ABOUT THE TEAM The Alignment Oversight team at OpenAI develops techniques for improving control, accountability, and alignment as AI systems become more capable and agentic. We combine longer-horizon research with hands-on deployment. We study long-term questions about how increasingly intelligent systems can be supervised, constrained, and corrected, while also building oversight systems that are used in practice today, both internally and externally (see our recent work on code review https://alignment.openai.com/scaling-code-verification/ and action monitoring for codex https://alignment.openai.com/auto-review/). We also study how to learn from real-world deployments: using oversight data and human interventions to train future models to be more aligned, while preserving the effectiveness and independence of the oversight systems themselves. ABOUT THE ROLE As a researcher on the Alignment team, you will design and run experiments that improve our ability to oversee increasingly capable models. You will work on hands-on model training, evaluation design, and research infrastructure, and translating promising oversight ideas into systems that can operate on real model traffic and real user workflows. This role combines longer-horizon research with shorter deployment sprints, with projects typically scoped around 3-6 month research timelines and aimed at directly improving future model behavior. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Design and implement alignment experiments focused on oversight systems for increasingly agentic AI models. - Deploy practical systems for action monitoring, red-teaming, and human-in-the-loop control. - Develop evaluations for alignment failure modes of the frontier models such as overeagerness, instruction following failures, covert actions, avoiding restrictions and scheming propensity. - Analyze deployment data to understand model failures, oversight gaps, and opportunities for training more aligned models. - Develop techniques for feeding oversight signals back into training while preserving the reliability and independence of the oversight process. - Produce externally publishable research when results advance the broader science of alignment. - Collaborate across research, product, security, safety, and engineering teams to turn alignment ideas into working systems. - Move quickly from research intuition to working experiments, prototypes, and evidence that can shape future models. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs. - Have experience with reinforcement learning, post-training, preference optimization, scalable oversight, model evaluation, or adjacent empirical ML research. - Have strong engineering execution and can turn ambiguous research ideas into reliable experiments, tools, training pipelines, and production-facing systems. - Have research intuitions for what experiments are likely to teach us something, while staying grounded in implementation details and empirical results. - Are a team player - willing to do a variety of tasks that move the team forward. - Enjoy fast-paced, collaborative research environments where priorities shift as models and evidence change. - See safety and usefulness as coupled goals. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal oppor

About the Team The Privacy Engineering team builds secure, reliable systems that help OpenAI meet its legal obligations while protecting user data. We partner closely with Legal and Engineering teams across OpenAI to support lawful data access requests and other critical legal workflows. Our work turns complex, high-stakes processes into auditable and dependable technical systems with clear human oversight and strong privacy and security controls. About the Role We’re looking for a full-stack Software Engineer to build the internal tools and data pipelines that power lawful data access request workflows and Legal Operations. You will work across product and data systems to make authorized retrieval and case handling accurate, efficient, and auditable. This role is well suited to someone who enjoys translating ambiguous operational requirements into durable systems, cares deeply about sensitive-data handling, and wants to improve both technical reliability and the day-to-day experience of the people operating these workflows. This role is based in San Francisco, CA, with two additional locations under consideration: London, UK, and Dublin, Ireland. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, build, and operate backend systems and workflow tooling for the full lifecycle of lawful data access requests, from intake and scoping through authorized retrieval, review, preparation, and audit. - Build reliable data pipelines and interfaces across products and data stores so authorized teams can locate and handle the right records accurately and reproducibly. - Implement least-privilege access, approval gates, provenance, audit trails, data minimization, and safe failure modes for sensitive workflows. - Partner with Legal and Legal Operations to translate legal and operational requirements into clear technical designs and intuitive operator experiences. - Identify responsible automation opportunities that reduce repetitive work while preserving human review, judgment, and accountability. - Own production systems through testing, observability, incident response, documentation, and continuous reliability improvements. - Help define the architecture and roadmap for reusable privacy and legal-infrastructure foundations as OpenAI’s products and obligations evolve. You might thrive in this role if you: - Have experience building or operating systems for lawful data access requests and understand the domain’s legal-process lifecycle, privacy and security constraints, auditability requirements, and operational sensitivities. - Strong backend engineering fundamentals and experience building production services or data-intensive systems. - Ability to reason carefully about correctness, authorization, security, and privacy when working with sensitive data. - A track record of turning ambiguous requirements into pragmatic plans and communicating technical tradeoffs clearly. - End-to-end ownership, including operating what you build, and comfort learning unfamiliar products and domains. - Care for operator experience and a drive to make complex workflows safer, clearer, and more efficient. - Experience collaborating across Engineering, Legal, operations, Privacy, and Security stakeholders. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, ag

ABOUT THE TEAM The CoT Monitorability team at OpenAI studies whether and when the chain-of-thought of frontier reasoning models is monitorable enough to support scalable oversight. We study how to measure monitorability https://openai.com/index/evaluating-chain-of-thought-monitorability/, which training mechanisms affect monitorability, and speculative methods to improve monitorability. While we mostly focus on CoT monitorability at the moment, we care more generally about any form of monitorability, auditing methods, and improving alignment. We were the first to show https://openai.com/index/chain-of-thought-monitoring/ that chain-of-thought monitoring can be a practical additional safety mechanism, and today our monitoring systems are actively used on OpenAI’s largest RL training runs to detect misbehavior. The issues we surface are then used to help improve our reward functions, environments, etc (without directly training against a CoT monitor). Our work sits in Alignment and intersects with model training, alignment evaluations, monitoring, and frontier-risk research.We care most about monitorability where the stakes are high, and about preserving useful oversight signals as models become more capable. ABOUT THE ROLE We’re looking for a researcher with strong empirical ML expertise and a deep interest in model behavior, alignment, or interpretability. Direct chain-of-thought interpretability experience is welcome but not required; strong candidates may come from broader interpretability, alignment, model training, or investigative model-behavior work. As a researcher on the Alignment team, you will design and run experiments that improve our understanding of model monitorability. You will investigate how training interventions across the model-development pipeline influence whether reasoning remains legible, build evaluations that make those questions measurable, and help translate findings into practical oversight and training recommendations. You may also help develop new monitoring models or methods and apply them to OpenAI’s largest training runs. This role is especially well suited for someone who can move from an ambiguous model-behavior question to a concrete experimental setup: formulate the hypothesis, build the evaluation or intervention, run the experiment, analyze the result, and decide what the evidence supports. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Design and run empirical studies of chain-of-thought monitorability across frontier reasoning models and training settings. - Build evaluations that measure whether monitors can reliably predict properties of interest, including high-stakes forms of misbehavior. - Investigate how pre-training, synthetic data, mid-training, post-training, reinforcement learning, and other interventions improve or degrade monitorability. - Analyze model behavior and turn observations from monitoring into hypotheses, experiments, and recommendations. - Translate research findings into practical monitoring and oversight approaches that can inform real training runs. - Collaborate with researchers and engineers across model training, alignment evaluations, monitoring, and frontier-risk work. - Produce externally publishable research when results advance the broader science of alignment. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs. - Have deep curiosity, interest in alignment, and high agency. - Bring depth in alignment, interpretability, model behavior, empirical ML, or adjacent research. - Are excited to investigate chain-of-thought monitorability, monitoring methods, and scalable oversight. - Can turn ambiguous research questions into measurable experiments and follow the evidence when results are subtle or noisy. - Move comfortably between research id

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. The team partners closely with research and product teams across the company, and conducts research as a final step to prepare for real world deployment to millions of users, ensuring that our models are safe, efficient, and reliable. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own and pursue a research agenda to improve model capability and performance. - Collaborate closely with the other research and product teams, allowing customers to optimize their own models. - Build robust evaluations for tracking modeling improvements. - Design, implement, test, and debug code across our research stack. You might thrive in this role if you: - Have a deep understanding of machine learning and machine learning applications. - Have a working knowledge of relevant models, and building evaluations for model capability improvement. - Are comfortable diving into a large ML codebase to debug. - Thrive in a dynamic and technically complex environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compliance. We are committed to providing reasonable accommodations to applicants with disa

ABOUT THE TEAM The Codex Research team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. ABOUT THE ROLE As a member of the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. IN THIS ROLE, YOU MIGHT: - Design and run experiments that improve agentic model behavior across coding, tool use, function calling, computer use, multi-agent collaboration, long-horizon tasks, factuality, instruction following, and calibrated reasoning. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex, API/platform, ChatGPT, and general-agent product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals,

ABOUT THE TEAM OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. ABOUT THE ROLE We’re seeking a Research-Hardware Codesign Engineer to operate at the boundary between model research and silicon/system architecture. You’ll help shape the numerics, architecture, and technology bets of future OpenAI silicon in collaboration with both Research and Hardware. Your work will include debugging gaps between rooflines and reality, writing quantization kernels, derisking numerics via model evals, quantifying system architecture tradeoffs, and implementing novel numeric RTL. This is a hands-on role for people who go looking for hard problems, get to ground truth, and drive it to production. Strong prioritization and clear, honest communication are essential. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. IN THIS ROLE YOU WILL: - Build on our roofline simulator to track evolving workloads, and deliver analyses that quantify the impact of system architecture decisions and support technology pathfinding. - Debug gaps between performance simulation and real measurements; clearly communicate root cause, bottlenecks, and invalid assumptions. - Write emulation kernels for low-precision numerics and lossy compression schemes, and get Research the information they need to trade efficiency with model quality. - Prototype numerics modules by pushing RTL through synthesis; hand off novel numerics cleanly, or occasionally own an RTL module end-to-end. - Proactively pull in new ML workloads, prototype them with rooflines and/or functional simulation, and drive initial evaluation of new opportunities or risks. - Understand the whole picture from ML science to hardware optimization, and slice this end-to-end objective into near-term deliverables. - Build ad-hoc collaborations across teams with very different goals and areas of expertise, and keep progress unblocked. - Communicate design tradeoffs clearly with explicit assumptions and confidence levels; produce a trail of evidence that enables confident execution. YOU WILL THRIVE IN THIS ROLE IF: - An exceptional track record of high-quality technical output, and a bias for shipping a prototype now and iterating later in the absence of clear requirements. - Strong Python, and C++ or Rust, with a cautious attitude toward correctness and an intuition for clean extensibility. - Experience writing Triton, CUDA, or similar, and an understanding of the resulting mapping of tensor ops to functional units. - Working knowledge of PyTorch or JAX; experience in large ML codebases is a plus. - Practical understanding of floating point numerics, the ML tradeoffs of reduced precision, and the current state of the art in model quantization. - Deep understanding of transformer models, and strong intuition for transformer rooflines and the tradeoffs of sharded training and inference in large-scale ML systems. - Experience writing RTL (especially for floating point logic) and understanding of PPA tradeoffs is a plus. - Strong cross-functional communication (e.g. across ML researchers and hardware engineers); ability to slice ambiguous early-incubation ideas into concrete arenas in which progress can be made. To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries

ABOUT THE TEAM The Alignment Science team at OpenAI studies the science of intent alignment: how to train models to understand what users are actually asking for, act faithfully on that intent while respecting safety constraints, verify what they did, and report their limitations honestly. Our work sits alongside broader value alignment efforts, but this team focuses on scalable methods for ensuring instruction-following, honesty, and robustness as models become more capable. We work on both sides of alignment research: producing externally publishable results and integrating promising techniques into the models OpenAI deploys. Recent team research on model confessions studies how models can be trained to honestly report shortcomings after their original answer, including failures involving hallucination, instruction following, scheming, and reward hacking. That work reflects a broader agenda: build scalable and general methods to ensure models follow human intent. The team uses a mix of training and evaluation methods, with a focus on reinforcement learning. We care about rigorous, quantitative research that can translate into safer model behavior. ABOUT THE ROLE As a Research Engineer / Research Scientist on the Alignment team, you will design and run experiments that help increasingly capable models follow user intent, remain calibrated about correctness and risk, and honestly surface their own mistakes. You will work on hands-on model training, evaluation design, and research infrastructure, while helping turn promising alignment methods into techniques that can be used in frontier model development. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. We are also open to exceptional remote candidates who can operate independently and collaborate closely with the team. IN THIS ROLE, YOU WILL: - Design and implement alignment experiments focused on intent following, honesty, calibration, and robustness. - Train and evaluate models using reinforcement learning, and other empirical ML methods. - Develop evaluations for failure modes such as hallucination, instruction-following failures, reward hacking, covert actions, and scheming. - Study methods that encourage models to verify their behavior and report shortcomings honestly, including confession-style training objectives. - Build monitoring and inference-time interventions that ensure compliant behavior or surface model issues to users or downstream systems. - Investigate how alignment methods scale with model capability, compute, data, context length, action length, and adversarial pressure. - Integrate successful techniques into model training and deployment workflows. - Produce externally publishable research when results advance the broader science of alignment. - Collaborate with researchers and engineers across post-training, RL, evaluations, safety, and product-facing teams. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong hands-on experience training, evaluating, or debugging large ML models, especially LLMs. - Have excellent engineering skills in Python and modern ML frameworks such as PyTorch. - Bring mathematical rigor, quantitative taste, and comfort turning ambiguous research questions into measurable experiments. - Have experience with reinforcement learning, post-training, preference optimization, scalable oversight, model evaluation, or adjacent empirical ML research. - Can operate with high independence and do not need close day-to-day handholding. - Enjoy fast-paced, collaborative research environments where priorities shift as models and evidence change. - Have a strong record in technical problem solving, such as competitive programming, math contests, systems work, or similarly rigorous engineering and research projects. - Care about building AI systems that are trustworthy, honest, and reliable in high-stakes settings. - Are motivated by making concrete

About the Team Our Safety Systems https://openai.com/safety/safety-systems team is at the forefront of OpenAI's mission to build and deploy safe AGI, driving our commitment to AI safety and fostering a culture of trust and transparency. The Model Policy team aligns model behavior with desired human values and norms. We co-design policy with models and for models by driving rapid policy taxonomy iteration based on data and defining evaluation criteria for foundational models’ ability to reason about safety. Key focus areas include: catastrophic risk, mental health, teen safety and multimodal safety. About the Role Providing access to frontier AI systems raises complex questions around dual-use science and catastrophic risk. How should models respond to requests involving chemical synthesis, biological experimentation, or pathogen research? Where is the boundary between legitimate scientific inquiry and information that could enable misuse? How do we design policies that meaningfully reduce risk without unnecessarily restricting beneficial research? This is a senior role in which you’ll help shape policy creation and development at OpenAI for addressing biological and chemical risks. You will develop structured policy frameworks and taxonomies to guide safe model behavior. This role sits at the intersection of biosecurity expertise, AI safety research, and policy design. You will help ensure that frontier AI systems can support beneficial life sciences research, such as drug discovery, public health, and biosafety, while reducing the risk that these capabilities could be misused. Our relevant publications: - Preparedness framework https://openai.com/index/updating-our-preparedness-framework/ - Preparing for future AI capabilities in biology https://openai.com/index/preparing-for-future-ai-capabilities-in-biology/ - Safety evaluations hub https://openai.com/safety/evaluations-hub/ - OpenAI GPT5 System Card https://openai.com/index/gpt-5-system-card/ - Evaluating Fairness in ChatGPT https://openai.com/index/evaluating-fairness-in-chatgpt/ - Improving Model Safety Behavior with Rule-Based Rewards https://openai.com/index/improving-model-safety-behavior-with-rule-based-rewards/ - OpenAI Model Spec https://openai.com/index/introducing-the-model-spec/ Your Responsibilities: - Design and maintain model policies governing chemical and biological risk, defining how models should safely handle dual-use scenarios. - Develop structured taxonomies of chemical and biological risk that inform model training data, evaluation benchmarks, and safety monitoring systems. - Translate biosecurity and chemical security expertise into actionable model behavior, working closely with research and engineering teams to operationalize policy in training and evaluation pipelines. - Develop a broad range of subject matter expertise while maintaining agility across topics. - Identify emerging risk vectors where frontier AI capabilities could meaningfully lower barriers to harmful activity and develop mitigation strategies. - Engage with internal and external subject-matter experts in biosecurity, biodefense, and chemical safety to ensure policies reflect real-world risk landscapes. You might thrive in this role if you: - Have strong domain expertise in chemistry, biology, biosecurity, or related fields and are motivated to translate that expertise into principled, operational policies that scale to frontier AI systems. - Have experience researching or working with LLMs, machine learning, AI governance, technology policy, or related areas, and enjoy tackling structured reasoning and classification problems—such as defining boundaries between legitimate scientific inquiry and potentially harmful applications. - Have experience designing, refining, or enforcing policies or safeguards for complex systems, whether in AI/ML environments, scientific research governance, national security contexts, or other high-stakes technical domains. - Are comfortable navigating a

About the Team We believe that increasing compute is a huge lever to AI progress. The Hardware team owns the design and/or sourcing of the compute, storage and interconnect hardware needed to build OpenAI’s supercomputers at the scale needed to deliver AGI that is beneficial to humanity. This includes: - Optimizing the processing hardware for AI models - Designing memory systems to keep up with the needs of training and inference - Enabling the scale-up and scale-out interconnect fabrics create the world’s most power supercomputers We work at the very cutting edge of speed and scale. You won’t encounter another organization with as much compute per employee. We are a small team that moves quickly, with access to huge resources, working with a direct impact on the success of OpenAI and, by extension, the field of AI as a whole. About the Role As a Hardware Chips Programs Manager at OpenAI, you will help bring our chips hardware roadmap to life, navigating an array of technical and partnership challenges. We’re looking for people excited to push the frontiers of computing by navigating technical explorations and are passionate about building. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. "To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations." In this role, you will: - Manage the design and implementation planning of our ML acceleration hardware, working across technical, cross-functional and external stakeholders - Lead planning and scheduling of chip hardware designs with our strategic partners and vendors - Coordinate and marshal internal resources and communication for efficient interaction with partners and vendors. You might thrive in this role if you: - Have experience as a technical program manager for data center hardware products (server, GPU, TPU, networking, storage and so on) - Know the whole end-to-end system program management from concept, design, production, deployment into the data center - Have some experience with System SW programs through NPI - Want to help design some of the world’s largest supercomputing systems, working at the edge of complex hardware challenges - Enjoy working with and enabling world-class AI Researchers and Engineers - Are passionate about the technical program function, and enjoy independently owning and delivering on your teams’ goals and cutting-edge problems in AI compute About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that crim

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: - Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. - Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. - Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. - Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large. You might thrive in this role if you: - Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. - Demonstrated experience in deep learning and transformers models - Experience with content understanding or abuse prevention with LLMs is a plus - Proficiency in frameworks like PyTorch or Tensorflow - Strong foundation in data structures, algorithms, and software engineering principles. - Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization - Excellent problem-solving and analytical skills, with a proactive approach to challenges. - Ability to work collaboratively with cross-functional teams. - Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines - Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employm

About the Team The Personal AGI team is responsible for training and improving pre-trained models to be deployed into ChatGPT, the API, and potential future products. In the Model Experience team, we shape the default character and behavior of ChatGPT: how the model communicates, responds to users, uses its capabilities, and behaves across different contexts and languages. Our goal is to make every interaction with ChatGPT thoughtful, helpful, and trustworthy. We take an opinionated view of what good human–AI interaction should look like, then turn that vision into real model behavior through human data, evaluations, reward models, and post-training. Our work sits at the intersection of research, product, and model design. We partner closely with teams across OpenAI to conduct research and ensure our models are thoughtful, safe, reliable to serve millions of users. About the Role As a Research Engineer / Scientist, you will research and develop improvements to our models. Our team works in research areas combining reinforcement learning and products. We're looking for individuals with strong ML engineering skills and research experience, especially with novel and highly capable models. An ideal candidate is passionate about product-driven research and the quality of human-AI interaction. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own and pursue a research agenda to improve model capability and performance. - Collaborate closely with the other research and product teams, allowing customers to optimize their own models. - Build robust evaluations for tracking modeling improvements. - Design, implement, test, and debug code across our research stack. You might thrive in this role if you: - Have a deep understanding of machine learning and machine learning applications. - Have good judgment about model behavior and can communicate this judgment effectively. - Enjoy taking ambitious, qualitative problems and turning them into concrete training interventions. - Have a working knowledge of relevant models, and building evaluations for model capability improvement. - Are comfortable diving into a large ML codebase to debug. - Thrive in a dynamic, technically complex, and collaborative environment. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: - Tracking and prediction. Monitoring https://openai.com/index/how-we-monitor-internal-coding-agents-misalignment/ and predicting the evolving misalignment propensities and capabilities of frontier AI systems. - Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. - Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE As a threat modeler, you will own OpenAI’s holistic approach to identifying, modeling, and forecasting frontier risks from frontier AI systems. This role ensures that our evaluation frameworks, safeguards, and taxonomies are robust, high-coverage, and forward-looking. You will help the company answer the “why” behind our most stringent risk-prevention efforts, shaping the rationale for prioritizing and mitigating risks across domains. You will serve as a central node connecting technical, governance, and policy perspectives on prioritization, focus and rationale on our approach to frontier risks from AI. IN THIS ROLE, YOU WILL: - Develop and maintain comprehensive threat models across all misuse areas (bio, cyber, attack planning, etc.). - Develop plausible and convincing threat models across loss of control, self-improvement, and other possible alignment risks from frontier AI systems - Forecast risks by combining technical foresight, adversarial simulation, and emerging trends. - Pair closely with technical partners on capability evaluations to ensure these map to and cover the gambit of severe risks differentially enabled by frontier AI systems. - Pair closely with Bio and Cyber Leads to size the remaining risk of the designed safeguards and translate threat models into actionable mitigation designs. - Act as the thought partner and explainer of “why” and “when” for high-investment mitigation efforts—helping stakeholders understand the rationale behind prioritization. - Serve as the central node connecting technical, governance, and policy perspectives on prioritization, focus and rationale on our approach to misuse risk. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Understand risks from frontier AI systems and have a strong grasp of AI alignment literature. Bring deep experience in threat modeling, risk analysis, or adversarial thinking (e.g., security, national security, or safety). - Know how AI evaluations work and can connect eval results to both capability testing and safeguard sufficiency. - Enjoy working across technical and policy domains to drive rigorous, multidisciplinary risk assessments. - Communicate complex risks clearly and compellingly to both technical and non-technical audiences. - Think in systems and naturally anticipate second-order and cascading risks. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional informatio

About the Team GTM Growth Engineering builds autonomous and semi-autonomous AI systems that help OpenAI's go-to-market organization operate at massive scale. We design agents and product systems that reason over messy GTM context, identify high-value opportunities, prioritize accounts and leads, route judgment-heavy work, take routine actions, and learn from every outcome. Our mandate is revenue leverage: systems directly tied to pipeline quality, revenue execution, sales productivity, and the speed at which OpenAI can bring its products to the world. The work sits at the intersection of product engineering, applied AI, data, and GTM operations. The team builds the infrastructure and user experiences for agentic revenue workflows: signal quality, prioritization, routing, attribution, review queues, feedback loops, evals, and measurement. We focus on problems that need native product craft, deep system integration, and high standards for autonomy, reliability, safety, privacy, and operational simplicity. About the Role We're looking for a product engineer to help build highly autonomous agentic systems for GTM Growth Engineering. You will own meaningful product slices end to end: agent workflows, user experience, frontend implementation, backend APIs and services, data and state models, model and tool integrations, telemetry, evals, and launch readiness. This is a role for engineers who want to build AI systems that do real work in production. You will partner with product, design, data, research, operations, and customer-facing teams to understand high-value workflows, define success metrics, and ship systems that improve pipeline quality, revenue execution, sales productivity, operational throughput, customer experience, and learning velocity. The role is ideal for a strong product engineer who can move between product craft, agent behavior, systems engineering, and measurable business outcomes. You should be excited to build from ambiguous problem statements, ship quickly, and harden systems that operate with increasing autonomy at scale. What You'll Do - Build autonomous and semi-autonomous GTM systems that identify opportunities, recommend or take next actions, route work, and learn from outcomes at scale. - Own full-stack product slices from prototype through launch, hardening, instrumentation, evals, and iteration. - Design agent workflows that combine LLM reasoning, tools, structured data, human oversight, and feedback loops. - Create intuitive surfaces for humans to supervise, review, correct, and improve AI-driven workflows. - Build reliable backend services, APIs, data flows, and stateful product surfaces that integrate with internal tools and customer-facing systems. - Design feedback loops, evals, quality metrics, and launch-readiness criteria for AI systems that affect revenue and pipeline outcomes. - Partner with product, design, data, research, sales, marketing, operations, support, and other GTM stakeholders to ship trustworthy products. - Instrument the experience so we can understand usage, friction, quality, adoption, business impact, and operational health. - Make pragmatic tradeoffs across autonomy, speed, quality, scalability, privacy, safety, and supportability in 0-to-1 product areas. What We're Looking For - Have 4+ years of experience as a software, product, or full-stack engineer building high-quality user-facing products. - Strong frontend or full-stack engineering skills, with comfort across modern web apps, APIs, data models, stateful user flows, and instrumentation. - Strong product judgment and a track record of turning ambiguous ideas into shipped product. - Experience building in 0-to-1 or fast-moving product environments where user needs, product shape, and success metrics are still being discovered. - Excitement about building AI systems that take action, use tools, make recommendations, coordinate with humans, and improve from feedback. - A high bar for UX quality, interaction details, acce

About the Team The Foundations Research team works on high-risk, high-reward ideas that could shape the next decade of AI. Our goal is to advance the science and data that enable our training and scaling efforts, with a particular focus on future frontier models. Pushing the boundaries of data, scaling laws, optimization techniques, model architectures, and efficiency improvements to propel our science. The Search team sits within Foundations, building agentic search by co-designing model–system interfaces with the core search stack (serving, indexing, retrieval) to translate model intent into reliable, real-world actions. Operating at the frontier of AI and information retrieval, the team develops large-scale systems that transform and index vast corpora, enabling models to reason over global knowledge and act dependably. In close partnership with researchers, we rapidly bring modeling breakthroughs into production and redefine how intelligent systems discover, retrieve, and synthesize information at planetary scale. About the Role We’re looking for a Software Engineer focused on building and scaling retrieval systems. You’ll work with a team of researchers and engineers to develop infrastructure that enables models to retrieve and act on the right information at the right time. This includes designing and operating indexing systems, retrieval pipelines, and serving layers. This work supports retrieval across OpenAI products and research, with direct impact on system performance, reliability, and scale. Responsibilities - Build and scale retrieval infrastructure across indexing, serving, and query execution. - Develop low-latency, high-throughput systems for real-time model interaction. - Partner with research to productionize embedding and retrieval techniques. - Support dense, sparse, and hybrid retrieval pipelines. - Own system performance, reliability, and observability at scale. - Collaborate across Pretraining, Inference, and Product teams to integrate retrieval end-to-end. - Contribute to model - system interfaces for agentic workflows. You Might Thrive in This Role If You Have - Experience building and scaling distributed systems. - Background in search, retrieval, or indexing systems. - Familiarity with embedding-based or ML-powered systems. - Experience with performance optimization and production reliability. - Ability to work across ML and systems boundaries. - First-principles thinking in ambiguous problem spaces. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resu

About the Team The Cooperative AI team is scaling OpenAI with OpenAI. We are building a model powered knowledge system that evolves and learns as our products, systems and customers evolve. We leverage our state of the art models, technologies, and products (some external, some still in the lab) to assist or completely automate robust operations supporting both internal and external customers. We support OpenAI customers and internal partners globally, powering systems from customer support to integrity to product insights. We are a self-contained multi-disciplinary team, who enjoy a lightning fast feedback loop with customers at scale, some of whom sit just a few pods away. We iterate fast, and engineer for reliable long-term impact. We're constantly looking for the similarities and patterns in different types of work, and focus on building simple primitives, to apply world class knowledge to many domains. The work of this team exemplifies use of OpenAI technologies. We build systems so everyone can see the leverage that is possible with well designed AI-based implementations. We do this by working through internal use cases focused on Customers (specifically knowledge systems, automation systems, and automated agent systems) to prove impact, then we scale. About the Role We’re looking for a Backend Software Engineer to help architect and scale the infrastructure that powers our knowledge systems. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. In this role, you will: - Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems - Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. - Collaborate closely with product, research, and engineering teams to integrate OpenAI models into high-leverage workflows - Own the full development lifecycle of new backend systems and internal platform capabilities - Build with scale and maintainability in mind, while rapidly iterating on new ideas You might be a great fit if you have: - 4+ years of backend engineering experience at product-driven companies (excluding internships) - Proficiency in backend technologies. Our tech stack includes Python, FastAPI, and Postgres - Experience designing and scaling distributed systems, APIs, or data processing pipelines - A pragmatic mindset. You’re comfortable shipping iteratively while building toward a long-term vision - An interest in structured knowledge representation, internal search, agent infrastructure, or systems that evolve over time Curiosity about AI/ML and excitement to work alongside world-class research and product teams (hands-on experience is a bonus, not a must) About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role We are seeking an experienced SoC Architect to lead the definition and development of next-generation custom AI silicon for edge deployments. This role will be responsible for shaping the architecture of highly efficient, high-performance SoCs optimized for machine learning inference and on-device intelligence. You will work cross-functionally with internal engineering teams and external ecosystem partners to translate product requirements into scalable silicon solutions, driving execution from concept through delivery. In this role you will: - Define the architecture and technical roadmap for custom SoCs targeted for edge applications. - Drive system-level tradeoff analysis across compute, memory, interconnect, power, thermal, and cost constraints. - Architect energy-efficient ML compute subsystems optimized for inference workloads and real-world deployment environments. - Collaborate with internal hardware, software, systems, and product teams to align architecture with platform needs. - Partner with external silicon vendors, IP providers, and manufacturing partners to execute development plans. - Lead hardware/software co-design efforts to maximize performance per watt and end-to-end system efficiency. - Guide implementation teams through microarchitecture, RTL development, validation, and bring-up phases. - Operate effectively in agile development environments and help teams deliver against aggressive schedules and milestones. You might thrive in this role if: - Proven experience defining and delivering complex SoC or ASIC architectures from concept to production. - Deep understanding of AI/ML accelerators, edge inference workloads, and energy-efficient compute design. - Strong knowledge of SoC subsystems including CPU/GPU/NPU architectures, memory hierarchies, interconnects, and power management. - Experience working with both internal engineering organizations and external strategic partners. - Ability to lead cross-functional teams in fast-paced, execution-driven environments. - Strong communication skills with the ability to influence technical direction across organizations. Preferred Qualifications - Experience with edge AI devices, embedded systems, or consumer hardware platforms. - Background in performance modeling, silicon cost optimization, and workload-driven architecture. - Familiarity with advanced process nodes and modern semiconductor development flows. To comply with U.S. export control laws and regulations, candidates for this role may need to meet certain legal status requirements as provided in those laws and regulations. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statem

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from - Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems - Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades - Supporting research workflows with service frameworks and deployment systems - Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching - Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. - Interface with researchers and product teams to understand workload requirements - Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: - Have experience with hyperscale compute systems - Possess strong programming skills - Have experience working in public clouds (especially Azure) - Have experience working in Kubernetes - Execution focused mentality paired with a rigorous focus on user requirements - As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data sec

About the Team The Fleet team builds core components to enable productive research from small to state of the art scale across OpenAI, with the goal of accelerating progress towards AGI. We frequently collaborate with other teams to speed up the development of new state-of-the-art capabilities. About the Role As we scale up with more researchers and engineers joining OpenAI, we seek a pragmatic and passionate engineer with a strong focus on the development experience for both engineers and scientists. In this role, you will be responsible for building and maintaining systems that allow our research + engineering organization to iteratively develop, test, and deploy new features reliably, with high velocity, and with a frictionless and fast development cycle. You will help oversee and drive to the vision of how we should build, test and deploy software. You will drive the design of our continuous integration pipelines, testing infrastructure, training and support around our build system. Our current environment relies heavily on Python, Rust, and C++, which you will take ownership of and strive to transform into a state of the art development experience for research. Ultimately, your role will be to provide the necessary tools and metrics to support our fast-paced culture and ensure a stable, scalable platform for growth, while also fostering a seamless and low friction experience for OpenAI’s research. This role is based in San Francisco, CA. For a San Francisco role, we use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. You might thrive in this role if you: - Have supported large monorepo development and deployment before - Are a proficient Python programmer working in large monorepos - Are proficient with Docker and Kubernetes - Experienced in CI/CD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=5

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: 1. Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. 2. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. 3. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework https://openai.com/index/updating-our-preparedness-framework/, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE Models are becoming increasingly capable—moving from tools that assist humans to agents that can plan, execute, and adapt in the real world. As we push toward AGI, cybersecurity becomes one of the most important and urgent frontiers: the same systems that can accelerate productivity can also accelerate exploitation. As a Researcher for cybersecurity risks, you will help design and implement an end-to-end mitigation stack to reduce severe cyber misuse across OpenAI’s products. This role requires strong technical depth and close cross-functional collaboration to ensure safeguards are enforceable, scalable, and effective. You’ll contribute directly to building protections that remain robust as products, model capabilities, and attacker behaviors evolve. IN THIS ROLE, YOU WILL: - Design and implement mitigation components for model-enabled cybersecurity misuse—spanning prevention, monitoring, detection, and enforcement—under the guidance of senior technical and risk leadership. - Integrate safeguards across product surfaces in partnership with product and engineering teams, helping ensure protections are consistent, low-latency, and scale with usage and new model capabilities. - Evaluate technical trade-offs within the cybersecurity risk domain (coverage, latency, model utility, and user privacy) and propose pragmatic, testable solutions. - Collaborate closely with risk and threat modeling partners to align mitigation design with anticipated attacker behaviors and high-impact misuse scenarios. - Execute rigorous testing and red-teaming workflows, helping stress-test the mitigation stack against evolving threats (e.g., novel exploits, tool-use chains, automated attack workflows) and across different product surfaces—then iterate based on findings. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have a passion for AI safety and are motivated to make cutting-edge AI models safer for real-world use. - Bring demonstrated experience in deep learning and transformer models. - Are proficient with frameworks such as PyTorch or TensorFlow. - Possess a strong foundation in data structures, algorithms, and software engineering principles. - Are familiar with methods for training and fine-tuning large language models, including distillation, supervised fine-tuning, and policy optimization. - Excel at working collaboratively with cross-functional teams across research, security, policy, product, and engineering. - Have significant experience designing and deploying technical safeguards for abuse prevention, detection, and enforcement at scale. - (Nice to have) Bring background knowledge in cybersecurity or adjacent fields. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectr

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Research Engineer, Distributed Data Systems, you will design and scale the infrastructure that powers large-scale multimodal training and evaluation at OpenAI. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI's rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable infrastructure in high-stakes environments. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security. - Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient. - Partner with researchers to deeply understand requirements and translate them into production-ready systems. - Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. You might thrive in this role if you: - Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. - Are detail-oriented and bring rigor to building and maintaining reliable systems. - Demonstrate excellent software engineering fundamentals and organizational skills. - Are comfortable with ambiguity and rapid change. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information

About the Team The Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training. We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings. Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models. About the Role We are looking for engineers to operate the next generation of compute clusters that power OpenAI’s frontier research. This role blends distributed systems engineering with hands-on infrastructure work on our largest datacenters. You will scale Kubernetes clusters to massive scale, automate bare-metal bring-up, and build the software layer that hides the complexity of a magnitude of nodes across multiple data centers. You will work at the intersection of hardware and software, where speed and reliability are critical. Expect to manage fast-moving operations, quickly diagnose and fix issues when things are on fire, and continuously raise the bar for automation and uptime. In this role, you will: - Spin up and scale large Kubernetes clusters, including automation for provisioning, bootstrapping, and cluster lifecycle management - Build software abstractions that unify multiple clusters and present a seamless interface to training workloads - Own node bring-up from bare metal through firmware upgrades, ensuring fast, repeatable deployment at massive scale - Improve operational metrics such as reducing cluster restart times (e.g., from hours to minutes) and accelerating firmware or OS upgrade cycles - Integrate networking and hardware health systems to deliver end-to-end reliability across servers, switches, and data center infrastructure - Develop monitoring and observability systems to detect issues early and keep clusters stable under extreme load - Be expected to execute at the same level as a software engineer You might thrive in this role if you: - Have deep experience operating or scaling Kubernetes clusters or similar container orchestration systems in high-growth or hyperscale environments - Bring strong programming or scripting skills (Python, Go, or similar) and familiarity with Infrastructure-as-Code tools such as Terraform or CloudFormation - Are comfortable with bare-metal Linux environments, GPU hardware, and large-scale networking - Enjoy solving fast-moving, high-impact operational problems and building automation to eliminate manual work - Can balance careful engineering with the urgency of keeping mission-critical systems running Qualifications - Experience as an infrastructure, systems, or distributed systems engineer in large-scale or high-availability environments - Strong knowledge of Kubernetes internals, cluster scaling patterns, and containerized workloads - Proficiency in cloud infrastructure concepts (compute, networking, storage, security) and in automating cluster or data center operations Bonus: background with GPU workloads, firmware management, or high-performance computing About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Emplo

About the Team The Post-Training Frontiers team creates the frontier agents OpenAI ships to the world. We do the reinforcement learning training for the agentic models we ship in Codex, ChatGPT, and the API (from o1 to 5.5). Our role consists of (1) shepherding all integrations that should go into the final RL run and deciding what can make it in, (2) babysitting and scaling the final run, and (3) building the research and infra for horizontal integrations, such as improving function calling, factuality, multi-agent capabilities, memory, calibrated thinking, etc. About the Role This role focuses on keeping our frontier RL training runs fast, reliable, and unblocked. You will work across engineering and infrastructure problems as they emerge, from scaling and orchestration issues to inference bottlenecks, numerical problems, and hardware failures, as well as supporting large horizontal integrations in the big run, like multi-agent capabilities or memory. This is a role for a strong generalist who quickly learns anything needed for the task, has high attention to detail, debugs deeply, and is motivated by fixing the highest-impact problem in front of the team. In this role, you will: - Keep large-scale RL training runs moving by jumping into the most urgent engineering and infrastructure problems. - Debug issues across training systems, inference, orchestration, scaling, and distributed infrastructure. - Solve hard technical problems at the boundary between research and engineering: scaling experiments, improving training reliability, debugging distributed systems, reducing latency and cost, and making new capabilities robust under real workloads. - Improve reliability and efficiency for RL training runs. - Help researchers who are developing infra-heavy integrations, such as multi-agent capabilities or memory. - Turn recurring operational issues into better tools, systems, processes, or abstractions. - Work closely with research, infrastructure, and partner teams during tight model run timelines. - Become useful quickly in messy, ambiguous areas where ownership matters more than a perfectly scoped project. - Debug failures that cut across model behavior, training data, RL systems, evaluation infrastructure, serving systems, and agent harnesses, then turn those failures into hypotheses, fixes, and durable improvements. You might thrive in this role if you: - Want to train and ship our frontier models and ensure we make agents genuinely useful for developers, enterprises, researchers, and everyday users. - Are a strong generalist engineer with experience in some layer of ML infrastructure. - Have worked on RL, inference, scaling, training systems, orchestration, or adjacent ML infrastructure. - Learn extremely quickly and are comfortable operating across unfamiliar layers. - Are a strong debugger with high ownership, low ego, and excellent communication. - Can land in a messy area with tight timelines, become useful quickly, and gradually raise the quality of the whole system. - Are energized by fast-moving environments where reliability, speed, and judgment matter. - Like building load-bearing systems and processes when that is what the team needs, even if the work is not glamorous. Nice to have: - Experience supporting large-scale model training, async RL systems, or high-throughput ML infrastructure. - Experience debugging distributed systems across GPUs, networking, orchestration, or inference stacks. - Background in performance optimization, scaling, or production-critical infrastructure. - Experience working directly with researchers or fast-moving model teams. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its cor

ABOUT THE TEAM The AI Deployment Management (ADM) team enables organizations to turn OpenAI products into real, sustained impact through world-class enablement and training execution. Our mission is to help customers successfully adopt and operationalize AI across their organizations. We partner with enterprises to translate the potential of OpenAI’s technology into durable capability—through structured training, technical enablement, and scalable deployment programs. By helping customers move from experimentation to production, the ADM team accelerates time-to-value, deepens product adoption, and helps make OpenAI indispensable to how organizations work. About the Role The AI Deployment Manager role is a specialist post-sales enablement role focused on delivering high-impact enablement and adoption services across OpenAI’s product suite. This role is responsible for designing and delivering technical enablement experiences that support a repeatable adoption framework– driving sustained activation, expanding breadth and depth of usage, and measurable business value across OpenAI’s product suite, including ChatGPT Enterprise, Codex, Agents, and the API. This includes helping customers understand and correctly apply the deployment harnesses, evaluation layers, and operational controls required for reliable use. This role blends deep technical fluency, instructional design, and customer advisory. You will lead live trainings, workshops, and adoption interventions for audiences ranging from hands-on builders to executive leaders, helping customers understand not just what OpenAI’s products can do, but how to use them effectively in real-world contexts. Success in this role means accelerating customer confidence, increasing product adoption, supporting successful launches of new product capabilities, and helping customers translate technical features into tangible outcomes. This role is based in our Tokyo Office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Own the technical enablement of OpenAI products, including ChatGPT Enterprise, Codex, Agents, and API capabilities, helping define effective enablement patterns that support adoption across customer segments - Lead customer training and enablement across the full customer lifecycle, from initial onboarding through expansion, optimization, and long-term adoption. - Design and deliver high-impact training engagements, including onboarding sessions, advanced capability trainings, executive briefings, hackathons, and hands-on workshops for audiences ranging from senior leaders to working teams. - Drive customer activation, sustained usage, and measurable business value through structured enablement and deployment programs designed for durable adoption at scale - Partner closely with Sales, AI Success Engineers, Solutions Engineering, and Product teams to ensure seamless handoff from pre- to post-sale and consistent customer experience. - Develop and refine reusable training assets, playbooks, and best practices based on patterns observed across customers and regions. - Gather customer feedback from training and enablement engagements, synthesize themes across accounts, and relay insights to internal stakeholders to inform product and program improvements. YOU’LL THRIVE IN THIS ROLE IF YOU: - Have 4+ years of experience in customer-facing or instructional roles, engaging C-level and senior technical audiences in complex enterprise environments. - Possess exceptional presentation and communication skills, particularly when conveying the value of technical concepts clearly to senior and executive-level audiences. - Strong technical depth across coding, agents, and APIs, with a practical understanding of how AI systems are built, evaluated, and operated in production, including RAG, evaluation strategies, fine-tuning, and key tradeoffs. - Proven experience leading structured technical trainings, s

About the Team The Statsig team at OpenAI https://openai.com?utm_source=chatgpt.com builds and operates the experimentation platform that powers product development, measurement, and decision-making across the company. We partner closely with product, engineering, and infrastructure teams to ensure experiments are trustworthy, statistically rigorous, and scalable to the needs of frontier AI products. Our mission is to help teams make better decisions through reliable experimentation. We care deeply about statistical correctness, pragmatic solutions, and building systems that researchers and engineers can trust at massive scale. The team operates at the intersection of experimentation methodology, data infrastructure, causal inference, and product analytics. We are looking for experienced experimentation experts who want to shape the future of experimentation in the AI era. About the Role We are hiring a Staff-level Data Scientist to help lead the evolution of OpenAI’s core experimentation platform. This role is focused on improving the statistical rigor, reliability, and practical usability of experimentation across the company. You’ll work on some of the hardest problems in online experimentation: sample ratio mismatch detection, variance reduction, bias mitigation, metric design, triggered analysis, heterogeneous treatment effects, sequential testing, and experimentation in complex ML systems. You’ll also help translate advanced statistical concepts into pragmatic systems and product experiences that teams can actually use. This is a highly technical individual contributor role with significant influence across methodology, platform architecture, and experimentation best practices. The ideal candidate combines deep statistical expertise with strong systems intuition and hands-on experience building or operating experimentation platforms at scale. In this role, you will: - Drive the statistical direction and technical strategy for OpenAI’s experimentation platform - Design and improve experimentation methodologies used across product and research teams - Build pragmatic solutions to real-world experimentation challenges, balancing rigor with operational simplicity - Improve the reliability and trustworthiness of experiment results, including detection and prevention of bias, logging issues, and data quality failures - Developscalable analytical systems and pipelines in Python and distributed compute environments - Partner with engineers and product teams to improve experiment design, metric quality, and decision-making practices - Lead investigations into complex experimentation anomalies and measurement failures - Establish best practices for experimentation governance, interpretation, and statistical correctness - Mentor other data scientists and raising the overall technical bar for experimentation and causal inference You might thrive in this role if you have: - Experience building, scaling, or operating experimentation platforms at a large technology company - Deep expertise in statistics, causal inference, and online experimentation methodology - Strong understanding of practical experimentation challenges in production systems - Experience with areas such as variance reduction, CUPED, sequential testing, SRM detection, metric design, or heterogeneous effects - Strong coding and systems skills in Python and large-scale data processing frameworks (e.g. Spark) - Experience designing analytical data models and scalable experimentation pipelines - Ability to communicate complex statistical concepts clearly to technical and non-technical audiences - Track record of influencing technical strategy through hands-on technical leadership - Experience in large-scale product experimentation, ML experimentation, ranking systems, marketplace systems, or similar high-scale experimentation domains is highly valued Workplace & Location This role is based in Bellevue. We use a hybrid work model and value in-person collaboration for techn

About the Team The GTM (Go-To-Market) Innovation team is an internal powerhouse revolutionizing how we engage customers through groundbreaking applications of our technology. As an incubator, we amplify the impact of Sales, Technical Success, Enablement, and Revenue Operations by deploying our technology at scale. This team applies advanced capabilities to real-world interactions — reshaping conversations with customers, learning from every exchange, and finding novel ways to show the value of our technology. About the Role We’re looking for Full Stack software engineers with a product mindset to join the GTM Innovation team. As a product engineer on this team, you’ll help OpenAI meet the world at scale. You’ll partner closely with go-to-market teams to understand their workflows, identify leverage points, and ship novel solutions using OpenAI’s API platform. You’ll move quickly from prototype to production, and your work will directly shape how customers experience our technology in the field. This role is ideal for engineers who want to be close to users, own end-to-end outcomes, and help define entirely new categories of enterprise software. In this role, you will: - Build high-impact applications and tools that accelerate OpenAI’s go-to-market efforts - Work across the full product lifecycle for GTM: prototype, iterate, ship, and maintain - Embed with Sales, Technical Success, and Revenue Operations to identify user needs and build for them - Apply OpenAI’s models in novel ways to solve real-world customer and internal workflow problems - Translate learnings into feedback for Applied and Research teams to inform product development You’ll thrive in this role if you: - Have 4+ years of experience as a software/ML/product engineer working on user-facing systems - Former founder, or early engineer at a startup who built a product from scratch is a plus - Are fluent in Python or JavaScript and comfortable building full-stack applications - Have built or prototyped LLM-powered workflows using the OpenAI API (or similar) - Take initiative, move quickly, and operate with a strong sense of ownership - Enjoy working closely with end users and shaping 0→1 products - Are collaborative, curious, and motivated to make an outsized impact at the frontier of AI About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (

About the team The AI Deployment Engineering team works closely with frontier startups. We are trusted advisors to, and thought partners with, startups to ensure that OpenAI’s technology is deployed safely and effectively, whilst also partnering with engineering, research, and product to turn those insights into evaluation systems, product improvements, and better model behavior. This team sits at the intersection of customer reality and model quality. We combine hands-on technical depth with strong product judgment, helping translate complex, high-value use cases into clear signals that can improve both the customer experience and the underlying systems. About the role We are seeking a technically proficient, product-minded engineer to help push the frontier of advanced AI with our strategic startup customers. You'll work with some of the most exciting AI startups in the world, helping them optimize their own systems and turning those learnings into durable improvements across OpenAI’s research and products. You will partner deeply on complex workflows, identify the gaps that matter, and help transform those gaps into reproducible evaluations, technical insights - helping shape OpenAI's research and product direction. This role is well suited to engineers who are equally comfortable debugging a workflow, iterating on prompts or agents, designing evaluations, and collaborating across research and product. You should be excited by ambiguous, high-impact problems and motivated by the opportunity to shape how advanced AI systems improve in practice. This role is based in Stockholm. In this role, you will: - Work directly with strategic startup customers to understand critical workflows, uncover failure modes, and identify high-impact opportunities for improvement. - Prototype and iterate on prompts, agents, and workflow designs to better understand system behavior and unlock customer value. - Synthesize and deliver valuable feedback to the Product and Research teams, turning real usage patterns into clear, reproducible evals, benchmarks, and technical artifacts that improve model and product quality and ensure customer-grounded learnings influence roadmap and model development. - Build repeatable tools, patterns, and evaluation approaches that raise the quality bar across multiple use cases. - Operate with strong judgment in ambiguous environments, balancing immediate technical problem-solving with longer-term system improvement. - Build relationships within the startup ecosystem, serving as a technical partner to both individual customers and the broader community. You’ll thrive in this role if you: - Have strong software engineering & AI fundamentals. For example, experience as a startup CTO, software engineer, ML engineer, Data Scientist or equivalent. Experience shipping production systems end-to-end is a strong plus. - Have experience as a technical founder, or engineer at an early stage startup - Have familiarity with, or interest in, model training pipelines and reinforcement learning. - Have experience building AI applications, agents, or evaluation systems, and can reason clearly about model behavior in complex workflows. - Are comfortable working directly with highly technical users and translating their challenges into concrete technical signals. - Can move fluidly between prototyping, debugging, evaluation design, and cross-functional collaboration. - Communicate clearly across technical and non-technical audiences. - Bring high agency, strong product sense, and a bias toward building durable improvements rather than one-off fixes. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mi

ABOUT THE TEAM The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team builds the data, environments, graders, training methods, and feedback loops that shape what OpenAI’s next agents can do and what they are like to work with, then carries those improvements through major training runs and into products used by people every day. ABOUT THE ROLE As a member of the Agent Post-training Personality team, you will help make OpenAI’s agents exceptional collaborators. You will study what makes an agent thoughtful, clear, perceptive, appropriately proactive, and genuinely easy to work with, then translate those insights into evals, training data, reward signals, and model improvements. We use “personality” to mean much more than writing style or general likability. It includes whether an agent understands what the user is trying to accomplish, communicates with good judgment, adapts to context, asks useful questions, handles disagreement honestly and takes initiative at the right moments. The goal is to create a strong, tasteful default that can adapt to different people and situations. This work combines behavioral research, product thinking, research and communication taste. You will collaborate with product teams, human experts, and researchers across post-training and pretraining to ensure that improvements survive the full training stack and reach the models people use every day. IN THIS ROLE, YOU MIGHT - Develop a rigorous understanding of what makes an agent a great collaborator across professional, creative, technical, and everyday work. - Turn qualitative judgments about model behavior into concrete hypotheses, evals, graders, and training interventions. - Study explicit and implicit user signals to understand which behaviors create trust, satisfaction, continued use, and successful outcomes. - Work with human experts and trainers to produce high-quality, tasteful rollouts and preference data that capture excellent collaborative behavior. - Improve reward models and RL objectives for model behaviors. - Work with pretraining and early-training teams on data mixtures, objectives, synthetic data, and other upstream choices that shape downstream personality. - Build sustainable pipelines for updating older training data as our understanding of excellent model behavior evolves. - Partner closely with ChatGPT, Codex, and other product teams to turn consumer insight into model improvements and validate them in real workflows. - Own projects end to end, from observing a subtle behavioral failure through experimentation, training, evaluation, and launch. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Think instinctively from the user’s perspective and care deeply about how models feel to work with, not only how they perform on benchmarks. - Can translate subjective-seeming product questions into falsifiable hypotheses and rigorous evaluations without losing the nuance that made the question important. - Care about preserving individuality, adaptability, and behavioral diversity rather than optimizing every model toward one narrow style. - Want to shape how frontier agents communicate, collaborate, and build trust with millions of people. - Have strong technical foundations in machine learning, software engineering, statistics, behavioral science, HCI, or a related field, and can quickly learn across u

About the Team The Integrity team at OpenAI is dedicated to ensuring that our cutting-edge technology is not only revolutionary, but also secure from a myriad of adversarial threats. We strive to maintain the integrity of our platforms as they scale. The Integrity team is at the front lines of defending against misuse in all its forms: content abuse, scaled attacks, and other actions that could undermine the user experience or harm our operational stability. About the Role As a Machine Learning Engineer in OpenAI's Integrity team, you will have the opportunity to work with some of the brightest minds in AI. You’ll work on state-of-the-art models and classifiers, experiment with new architecture and approaches, and push forward our abilities in content and user understanding. You’ll help turn research breakthroughs into tangible solutions that improve the trust and safety of our platform. If you're excited about training LLMs and building ML models, this role is your chance to make a significant mark. In this role, you will: - Innovate and Deploy: Design and deploy advanced machine learning models that solve real-world problems. Bring OpenAI's research from concept to implementation, creating AI-driven applications with a direct impact. - Collaborate with the Best: Work closely with researchers, software engineers, and product managers to understand complex business challenges and deliver AI-powered solutions. Be part of a dynamic team where ideas flow freely and creativity thrives. - Optimize and Scale: Implement scalable data pipelines, optimize models for performance and accuracy, and ensure they are production-ready. Contribute to projects that require cutting-edge technology and innovative approaches. - Learn and Lead: Stay ahead of the curve by engaging with the latest developments in machine learning and AI. Take part in code reviews, share knowledge, and lead by example to maintain high-quality engineering practices. - Make a Difference: Monitor and maintain deployed models to ensure they continue delivering value. Your work will directly influence how AI benefits individuals, businesses, and society at large. You might thrive in this role if you: - Master's/ PhD degree in Computer Science, Machine Learning, Data Science, or a related field. - Demonstrated experience in deep learning and transformers models - Experience with content understanding or abuse prevention with LLMs is a plus - Proficiency in frameworks like PyTorch or Tensorflow - Strong foundation in data structures, algorithms, and software engineering principles. - Are familiar with methods of training and fine-tuning large language models, such as distillation, supervised fine-tuning, and policy optimization - Excellent problem-solving and analytical skills, with a proactive approach to challenges. - Ability to work collaboratively with cross-functional teams. - Ability to move fast in an environment where things are sometimes loosely defined and may have competing priorities or deadlines - Enjoy owning the problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employm

About the Team OpenAI’s Inference team powers the deployment of our most advanced models - including our GPT models, 4o Image Generation, and Whisper - across a variety of platforms. Our work ensures these models are available, performant, and scalable in production, and we partner closely with Research to bring the next generation of models into the world. We're a small, fast-moving team of engineers focused on delivering a world-class developer experience while pushing the boundaries of what AI can do. We’re expanding into multimodal inference, building the infrastructure needed to serve models that handle image, audio, and other non-text modalities. These workloads are inherently more heterogeneous and experimental, involving diverse model sizes and interactions, more complex input/output formats, and tighter coordination with product and research. About the Role We’re looking for a software engineer to help us serve OpenAI’s multimodal models at scale. You’ll be part of a small team responsible for building reliable, high-performance infrastructure for serving real-time audio, image, and other MM workloads in production. This work is inherently cross-functional: you’ll collaborate directly with researchers training these models and with product teams defining new modalities of interaction. You'll build and optimize the systems that let users generate speech, understand images, and interact with models in ways far beyond text. In this role, you will: - Design and implement inference infrastructure for large-scale multimodal models. - Optimize systems for high-throughput, low-latency delivery of image and audio inputs and outputs. - Enable experimental research workflows to transition into reliable production services. - Collaborate closely with researchers, infra teams, and product engineers to deploy state-of-the-art capabilities. - Contribute to system-level improvements including GPU utilization, tensor parallelism, and hardware abstraction layers. You might thrive in this role if you: - Have experience building and scaling inference systems for LLMs or multimodal models. - Have worked with GPU-based ML workloads and understand the performance dynamics of large models, especially with complex data like images or audio. - Enjoy experimental, fast-evolving work and collaborating closely with research. - Are comfortable dealing with systems that span networking, distributed compute, and high-throughput data handling. - Have familiarity with inference tooling like vLLM, TensorRT-LLM, or custom model parallel systems. - Own problems end-to-end and are excited to operate in ambiguous, fast-moving spaces. Nice to Have: - Experience working with image generation or audio synthesis models in production. - Exposure to distributed ML training or system-efficient model design. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the

About the Team OpenAI’s Compute organization turns ambitious AI research into real-world capability by delivering the compute infrastructure behind our most advanced models. The team works across software, hardware, facilities, operations, and engineering disciplines to make enormous amounts of compute available, reliable, and efficient. As the demand for frontier AI grows, so does the complexity of the systems required to support it. Scaling this infrastructure means solving problems that cut across distributed systems, ML infrastructure, GPU fleets, power, cooling, networking, manufacturing, supply chain, and data center delivery. Our work is focused on expanding the compute foundation that enables OpenAI to train more capable models, including systems like GPT-5.6, and make frontier AI available to more people, products, and workflows. We’re looking for exceptional people across many disciplines to help build the next generation of AI infrastructure at a scale few organizations have attempted. About the Role We are hiring across a broad range of roles to help design, build, scale, and operate OpenAI’s compute infrastructure. Depending on your background, you may work on large-scale distributed systems, ML infrastructure, hardware systems, manufacturing, supply chain, data center development, or the physical engineering systems required to bring massive compute capacity online. You’ll work with teams across research, engineering, hardware, operations, and infrastructure to solve high-impact problems at extraordinary scale. This may include improving system reliability, accelerating deployment timelines, increasing operational efficiency, designing new infrastructure, or helping bring new compute platforms and facilities from concept to production. This is an opportunity to work on one of the most important infrastructure challenges in AI: building the compute foundation required to train and serve increasingly capable frontier models. Key Responsibilities - Help build, scale, and operate OpenAI’s global compute infrastructure. - Solve complex problems across software, hardware, manufacturing supply chain, and data center systems. - Improve the reliability, performance, efficiency, and scalability of critical infrastructure. - Partner with cross-functional teams to bring new compute capacity online quickly and reliably. - Identify bottlenecks across technical, operational, and physical systems, and develop practical solutions. - Build tools, processes, systems, or infrastructure that improve execution at scale. - Contribute to the long-term architecture and operational maturity of OpenAI’s compute footprint. Qualifications - Have experience building, scaling, or operating complex technical systems. - Enjoy working on ambiguous, high-impact problems where the path forward is not always defined. - Are comfortable collaborating across disciplines, including software, hardware, operations, and physical infrastructure. - Have strong technical judgment and a bias toward execution. - Care deeply about reliability, speed, safety, and operational excellence. - Are excited by the challenge of building infrastructure at unprecedented scale. - Want your work to directly support the development and deployment of frontier AI. Preferred Skills - Have experience with AI infrastructure, high-performance computing, distributed systems, GPU clusters, or cloud-scale platforms. - Have worked on hardware systems, manufacturing, supply chain, data center development, or large capital infrastructure projects. - Have domain expertise in civil, controls, mechanical, hardware, electrical, thermal, power, networking, or facilities engineering. - Have helped bring new technical platforms, data centers, factories, or large-scale systems from concept to production. - Have experience operating in fast-moving environments where technical depth and execution speed both matter. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring

ABOUT THE TEAM OpenAI Finance is responsible for ensuring the organization is set up for success in pursuit of its mission. Within Finance, the Procurement team serves as a trusted advisor to the business, optimizing investments, securing essential resources, and enabling OpenAI’s mission through efficient and effective procurement practices. The Extended Workforce team helps OpenAI access specialized and flexible talent while creating a consistent, compliant, and high-quality experience for hiring managers, workers, vendors, and internal partners. As part of an AI-native organization, we are also rethinking how extended workforce programs should operate, using AI, automation, data, and new ways of working to reduce friction, improve decision-making, and build more scalable workforce solutions. Our goal is not simply to modernize traditional contingent workforce practices, but to help define what best-in-class extended workforce management looks like in an AI-first company. ABOUT THE ROLE We’re looking for an experienced, hands-on Extended Workforce Program Manager to operate and continuously improve key elements of OpenAI’s extended workforce program. Reporting to the Head of Extended Workforce, you will be a trusted partner responsible for translating program priorities into clear plans, scalable solutions, and measurable outcomes. This is an individual contributor role with significant cross-functional ownership and influence. You will take ownership of complex workstreams, solve ambiguous operational challenges, and partner closely with our Extended Workforce Operations team, Global Compliance Lead, and cross-functional stakeholders to strengthen the systems, workflows, and partnerships that enable the program to scale globally. While operational excellence is at the heart of this role, we are equally excited about what comes next. We believe AI presents an opportunity to fundamentally rethink how extended workforce programs operate. We are looking for someone who enjoys challenging conventional thinking, experimenting with new ideas, and helping build a more intelligent, automated, and scalable operating model for the future. This role is based in San Francisco, CA. We use a hybrid work model of three days per week in the office and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Partner with the Head of Extended Workforce to set direction for assigned workstreams, then own their end-to-end execution by translating priorities into clear plans, milestones, and measurable outcomes. - Partner closely with the Extended Workforce Operations team and Global Compliance Lead to ensure program operations are efficient, scalable, and aligned with compliance requirements. - Advise hiring managers and business stakeholders on workforce solutions, exercising sound judgment across stakeholder experience, speed, cost, compliance, risk, and operational scalability. - Translate business needs, stakeholder feedback, and operational insights into improved workflows, automation, systems, reporting, and user experiences. - Identify, test, and implement practical applications of AI, automation, analytics, and decision-support tools that reduce manual work, improve decisions, and enable a more scalable operating model. - Identify root causes behind recurring operational challenges and build durable processes, systems, and frameworks that prevent them from recurring. - Manage strategic supplier relationships to drive optimal performance, strengthen service delivery, address gaps, and ensure partners continue to meet OpenAI’s evolving workforce needs. - Establish program health measures and operational insights that identify systemic issues, inform priorities, and drive measurable improvements in service, efficiency, adoption, supplier performance, and risk. - Lead the rollout and adoption of new processes and tools, coordinating testing, documentation, training, communications, and success measurement. - Independently res

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, Artifacts, you will train frontier models to create polished, useful work products: documents, spreadsheets, slide decks, dashboards, reports, analyses, and other interactive or editable artifacts. You will help teach our models to move from a vague user goal to a finished artifact with strong structure, visual taste, domain judgment, correctness, and low latency. This work will require owning improvements across our post-training stack, including RL, data pipelines, graders, reward signals, evals, and behavioral analysis. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you will: - Design and run experiments that improve agentic model behavior for complex software and plugins.. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. You might thrive in this role if you: - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and engineering execution. - Care about product impact and model behavior, not just benchmark movement. You have opinions about what makes an agent useful, reliable, honest, tasteful, and easy to wor

ABOUT THE TEAM OpenAI’s Safety teams work to ensure our products are safe, trusted, and resilient as frontier AI systems scale globally. We tackle some of the company’s most important challenges across understanding and preventing misuse and misalignment, intercepting fraud and abuse, and protecting vulnerable users. We are hiring Data Scientists to help build the analytical foundations that allow OpenAI to deploy increasingly capable AI responsibly. We are hiring Data Scientists across several teams that contribute to safety in different ways, including: - Safety Systems - Integrity - Product Policy This is a high-impact role operating at the intersection of product, safety, policy, and research. About the Role As a Data Scientist, Safety, you will help solve complex and ambiguous problems where rigorous analysis directly informs critical decisions. Depending on your background and team alignment, you may work on areas such as: - Measure harmful or abusive behavior across OpenAI’s products - Detect fraud, manipulation, coordinated misuse - Evaluate and improve safety classifiers, rules systems, mitigation systems, and human review workflows - Design experiments and causal analyses to understand product, policy, and mitigation impacts - Build prevalence estimators, dashboards, monitoring systems, and executive decision frameworks - Diagnose gaps in safety and integrity systems using behavioral and product data, and help quantify and navigate false positive / false negative tradeoffs - Translate ambiguous safety risks into measurable problems and evidence-based recommendations - Partner with Product, Engineering, Policy, Research, and Operations teams to improve safety outcomes - Build zero-to-one analytical systems in rapidly evolving domains Ideal Candidate We’re looking for strong Data Scientists who thrive in ambiguous, high-leverage environments. You may be a fit if you have: - Strong statistical reasoning and analytical judgment - Experience with experimentation, causal inference, or observational analysis - Strong SQL and Python skills - Experience working with messy, incomplete, or noisy datasets - Ability to structure open-ended business or risk problems - Excellent communication with technical and non-technical stakeholders - High ownership and comfort operating independently Helpful backgrounds include: - Trust & Safety / Integrity - Fraud & abuse - Security analytics - AI/ML model measurement and evaluation - Alignment and AI safety research - Biosecurity, synthetic biology, infectious diseases, or computational biology Why This Role - Work on mission-critical problems with world-level impact - Help shape how frontier AI systems are deployed safely - Operate with unusual ownership and visibility - Solve novel problems where there are no existing playbooks - Join highly collaborative teams working across OpenAI Location San Francisco or New York depending on team alignment and business need. Compensation Range: $230K - $325K USD About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administere

About the Team OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture, datasets and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. Recent examples of artifacts with major contributions from our team include GPT4-Turbo, GPT-4o and o1-mini. About the Role As a member of the architecture team, you will push the frontier of architecture development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, prototype and scale up new architectures to improve model intelligence - Execute and analyze experiments autonomously and collaboratively - Study, debug, and optimize both model performance and computational performance - Contribute to training and inference infrastructure You might thrive in this role if you: - Have experience landing contributions to major LLM training runs - Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion - Are motivated by safely deploying LLMs in the real world - Are well-versed in the state of the art transformer modifications for efficiency About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and pr

About The Team Our mission is to bring OpenAI products to life for every customer. Demo Experience equips customer-facing teams with the experiences, systems, and confidence to make frontier capabilities tangible, relevant, and trustworthy. OpenAI’s products and customer needs are evolving rapidly. Demo Experience closes the gap between a frontier capability and a credible customer experience—making new capabilities understandable, demonstrable, and reusable quickly at scale. Working across Product, Engineering, Marketing, Operations, and GTM, we turn recurring customer needs into reusable capabilities and raise the standard for every customer conversation. About The Role Demo Experience Engineers work at the intersection of product engineering, technical storytelling, and GTM execution. You will own ambiguous, high-leverage problems end to end—from building agentic prototypes to creating the infrastructure and self-service tools that make them reliable and reusable. Your work will help customer-facing teams move faster, reduce avoidable failures, and translate frontier product capabilities into clear customer value. You will also turn recurring patterns from customer-facing work into product feedback, launch-readiness improvements, and scalable systems. Success in this role means teams can demonstrate new capabilities sooner and with greater confidence. Recurring requests become reusable capabilities instead of one-off work. Demo experiences are accurate, reliable, and safe. Insights from customer-facing work improve product and readiness decisions. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In This Role, You Will - Own end-to-end demo readiness for new and priority product capabilities, including environments, integrations, synthetic data, evaluations, reliability checks, and fallback paths. - Build compelling prototypes, LLM agents, and reference flows that make complex capabilities tangible and connect them to clear customer outcomes. - Convert recurring needs into reusable accelerators—including companion apps, templates, LLM Skills and Plugins, and self-service demo packages—that scale across customer-facing teams. - Work alongside GTM partners on high-impact customer moments, unblock critical technical gaps, and identify the patterns that should scale. - Build always-on internal agentic systems that automate demo preparation, validation, and asset maintenance for the Demo Experience team. - Translate recurring feedback into product insights, launch-readiness priorities, and systemic improvements with Product and Engineering. - Define and raise the bar for demo quality across accuracy, safety, reliability, usability, and adoption. You’ll Thrive In This Role If You - Care deeply about creating exceptional demo experiences and helping customer-facing teams translate OpenAI’s product value into customer understanding, trust, and action. - Are a product-minded engineer who can move from an ambiguous capability to working software and then harden it into a reliable, reusable system. - Have a track record of building compelling demos, reusable technical assets, or tooling that accelerates adoption and improves execution. - Understand when a customer needs a bespoke solution and when it should become a shared platform capability. - Bring strong engineering depth across software architectures, integrations, data, LLM agents, skills, plugins, or other AI-powered systems. - Thrive in rapidly evolving, ambiguous environments and influence effectively across Product, Engineering, Marketing, Operations, and GTM through curiosity, humility, and strong judgment. - Maintain a strong commitment to AI safety, responsible deployment, and representing OpenAI’s products accurately and credibly. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of

ABOUT THE TEAM The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. ABOUT THE ROLE As a member of this API & power-users team, you will improve the capabilities, reliability, and product fit of OpenAI’s agentic models for power users and API developers. You might design evals from real developer workflows, build training environments around production-like tool use, turn qualitative model failures into training data, evals, or post-training interventions, or drive a behavior improvement from discovery through post-training, integration, and launch. This role is intentionally broad. The strongest candidates are comfortable turning ambiguous model behavior problems into concrete progress, whether that means improving tool use, planning, instruction following, recovery from mistakes, or how models behave in API-based workflows. You should be excited to work across research, engineering, data, evals, and product to make models better at acting in real workflows. You will work closely with researchers, engineers, API/product teams, Codex, infrastructure, and safety/alignment partners to decide which behaviors matter, how to measure them, how to train them, and when they are ready for major model runs. This is a high-agency role for people who want their work to show up directly in frontier models used by expert users and developers. IN THIS ROLE, YOU MIGHT - Design and run experiments that improve model behavior in API and power-user workflows: function calling, tool use, coding, planning, long-horizon execution, factuality, instruction following, error recovery, and calibrated reasoning. - Build evals, graders, and environments from real developer and power-user workflows, then turn observed failures into training data, model-behavior hypotheses, and shipped improvements. - Partner with API and power-users to identify high-leverage behavior gaps and convert product signals into post-training interventions. - Improve how models behave when composed into systems: using tools reliably, respecting developer intent, handling partial failures, asking for clarification when appropriate, and maintaining coherence across multi-step tasks. - Own end-to-end model behavior projects, from qualitative failure analysis through data generation, training experiments, eval design, integration into major runs, and launch readiness. - Develop feedback loops that use power-user traces, API usage patterns, and production-like environments to discover the next frontier of agentic model failures and gaps. - Help decide which agentic capabilities, behavioral fixes, and partner-team integrations are ready for inclusion in major model runs. - Debug hard failures in shipped or near-shipped models by moving between traces, evals, training data, model outputs, and product context. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, c

ABOUT THE TEAM The Synthetic RL team develops reinforcement learning methods that leverage synthetic data, environments, and feedback to train and evaluate frontier AI models. The team explores approaches such as self-play, simulators, and other synthetic evaluations to push model capability, generalization, and alignment beyond what is possible with the current prevailing methodology. ABOUT THE ROLE As a Research Scientist on the Synthetic RL team, you will develop novel reinforcement learning techniques that use synthetic environments and feedback to improve large-scale models. You’ll work closely with other researchers to design experiments, analyze learning dynamics, and translate research insights into training approaches used in production systems. We’re looking for researchers who enjoy working on open-ended problems, value fast iteration, and want their work to directly shape how frontier models are trained. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Research and develop reinforcement learning algorithms - Design and run experiments to study training dynamics and model behavior at scale - Collaborate with engineers and researchers to integrate successful approaches into model training pipelines YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have a strong background in reinforcement learning, machine learning research, or related fields - Have strong engineering and statistical analysis skills - Enjoy exploring new problem spaces where data, objectives, and evaluation are imperfect or evolving - Are motivated by seeing research ideas influence real-world AI systems About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations. To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form https://form.asana.com/?d=57018692298241&k=5MqR40fZd7jlxVUh5J-UeA. No response will be provided to inquiries unrelated to job posting compl

ABOUT THE TEAM We’re hiring software engineers to make OpenAI’s Model Performance teams more productive. These teams work on the systems, tooling, and infrastructure that help improve model performance across OpenAI’s training and inference workloads at frontier scale. ABOUT THE ROLE We’re looking for an autonomous, high-ownership developer productivity engineer who cares deeply about helping other engineers move faster, safer, and with more confidence. This role will sit within OpenAI’s Model Performance organization, contributing to developer infrastructure, CI systems, testing workflows, tooling, and broader performance infrastructure efforts. There is also a strong opportunity to contribute to the Triton project and help improve the systems that support performance-critical engineering work across OpenAI. In this role you will: - Improve development workflows for engineers working on model performance infrastructure - Design and improve CI/CD, release, validation, and testing pipelines - Build and maintain tools that improve reliability, iteration speed, and engineering confidence - Partner closely with engineers to identify friction in testing, debugging, deployment, and development workflows - Contribute to infrastructure efforts that support performance-critical training and inference systems - Help improve developer experience across Python-heavy codebases and performance-oriented infrastructure - Work in a high-context, ambiguous environment where ownership and good judgment matter You might thrive in this role if: - You are motivated by enabling the people around you and helping engineers do their best work - You have strong experience with CI/CD, developer infrastructure, testing systems, tooling, or build/release workflows - You are highly collaborative, empathetic, and comfortable partnering deeply with technical teams - You are strong in Python and enjoy building reliable, scalable developer tools and infrastructure - You have experience improving large-scale engineering workflows, especially around CI reliability, test infrastructure, and debugging velocity - You are self-directed and comfortable operating with ambiguity - You do not need direct inference or model performance experience, but you are excited to learn the domain and make the team meaningfully more effective - Experience in the PyTorch ecosystem is highly relevant - Experience with C++ or Rust is a nice-to-have, but not required - When you see repeated friction — slow tests, flaky CI, brittle release processes, painful debugging, unclear validation — your instinct is to fix the underlying system - You are pragmatic and know how to balance high standards with forward progress About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fai

ABOUT THE TEAM OpenAI’s AI Success Engineer team partners with the world’s most ambitious government & partner organizations to translate cutting edge AI into real business and mission impact for governments of all levels from Local, State, Federal, and International. We guide customers and users journey from the first time they try ChatGPT Enterprise, automate a workflow, develop and execute a new skill, and create their first agent to scaled enterprise adoption of ChatGPT, Codex, our API and other novel capabilities. Our work spans technical integration and enablement, workflow transformation, inspiring and upskilling AI literacy and confidence across the workforce, sustained program, product and new capability delivery. Most importantly, we help each member of our customer's workforce, their teams, programs and missions meet their total potential. Our government customers have vital missions, and we must meet them with game-changing technology. Every engagement is an opportunity to shape how AI changes work, productivity, and innovation. This role sits at the center of that mission. ABOUT THE ROLE Governments work at a scale that is truly exponential on missions that are of critical importance to people, communities and nations. The AI Success Engineer role is the primary post-sales relationship for OpenAI’s most important customers. You are responsible for the end-to-end account management of critical Government and Partner customers. You will be helping Government Leaders/Partners appropriately and effectively use AI for their mission, while simultaneously investing in ensuring their people are AI-enabled and ready to advance positive outcomes that their constituents depend on them for. You will drive: the impact of our tools on their mission, account health and adoption, ensuring technical readiness, creating and executing on the deployment strategy, enabling, educating and training their workforce, identifying new use cases and upsell opportunities, and delivering measurable value to our customers with OpenAI’s ambitiously growing capabilities. This role blends technical depth, program and account management, customer advisory, training and enablement and product influence. You will partner deeply with customer teams, map workflows, lead configuration, oversee deployment plans, and guide customers toward high impact use cases that showcase the ways OpenAI tools can make a difference to the mission.. You drive our customers’ success and journey in an AI age. You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer use and value from our tools, guiding strategic use cases that get to production, and helping customers demonstrate tangible business and mission impact. You will bring key product feedback and insights to our product teams to ensure our capabilities continue to advance our customers' mission. IN THIS ROLE, YOU WILL: - Lead the relationship for post-sale customers and act as their trusted advisor on technical deployment, adoption, and value realization, this includes setting up, configuring and running API instances of our products. - Own customer success: account strategy & health; breadth, depth, velocity of adoption that drives mission impact, enablement and education; and ongoing technical deployment and success across your portfolio. - Be an expert in all of OpenAI products across our API and agentic platform, Codex, ChatGPT Enterprise, and more and conduct technical enablement and configuration sessions across them. - Train, educate and enable ChatGPT users to drive adoption and value. - Create and show customers how to make custom GPT’s, Skills, Agents, Plugins, Connectors, Codex and use all of the features and capabilities of our tools. - Design and lead hands-on activities like workshops, hackathons, and training sessions acr

ABOUT THE TEAM OpenAI’s mission is to ensure that artificial general intelligence (AGI) benefits all of humanity. A key part of achieving that mission is training models that deeply understand and reflect human preferences — the Human Data team is at the heart of that effort. The Human Data engineering team creates the systems that enable scalable, high-quality human feedback. These systems are essential to how OpenAI trains and improves its most advanced models. Engineers on this team collaborate closely with world-class researchers to bring alignment techniques to life — from experimental ideas to production-ready feedback loops. ABOUT THE ROLE We’re looking for software engineers to join the Human Data team and build the platforms, prototypes, tools, and infrastructure that power how our AI models are trained, aligned, and evaluated. You’ll partner with researchers and cross-functional teams to bring alignment ideas to life, influence future model training, and shape how models interact with the real world. We’re looking for people who are excited by technical ownership, enjoy working across the stack, and are eager to solve ambiguous problems in a high-impact, fast-paced environment. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Build and maintain robust full-stack systems for feedback collection, data labeling, and evaluation pipelines, while maintaining high levels of security. - Translate experimental alignment research into scalable production infrastructure, including inference and model training stacks. - Design and iterate on user-facing tools and backend services to support high-quality data workflows - Partner with researchers, engineers, and program leads to shape feedback loops and model interaction paradigms - Drive infrastructure improvements that enable faster iteration and scaling across OpenAI’s frontier models, from internal research tooling all the way to production ChatGPT. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have strong software engineering fundamentals and experience building production systems at scale - Enjoy full-stack development with end-to-end ownership — from backend pipelines to user interfaces - Are motivated by high-impact collaboration with research teams and solving novel, ambiguous problems - Are excited to shape how AI systems learn from human preferences and reflect a broad range of human values - Care deeply about inclusive tooling and building systems that enhance model safety, reliability, and usefulness About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County

About the Team Training Runtime designs the core distributed machine-learning training runtime that powers everything from early research experiments to frontier-scale model runs. With a dual mandate to accelerate researchers and enable frontier scale, we’re building a unified, modular runtime that meets researchers where they are and moves with them up the scaling curve. Our work focuses on three pillars: high-performance, asynchronous, zero-copy tensor and optimizer-state-aware data movement; performant, high-uptime, fault-tolerant training frameworks (training loop, state management, resilient checkpointing, deterministic orchestration, and observability); and distributed process management for long-lived, job-specific and user-provided processes. We integrate proven large-scale capabilities into a composable, developer-facing runtime so teams can iterate quickly and run reliably at any scale, partnering closely with model-stack, research, and platform teams. Success for us is measured by raising both training throughput (how fast models train) and researcher throughput (how fast ideas become experiments and products). About the Role As a Training: ML Framework Engineer, you will work on improving the training throughput for our internal training framework, while enabling researchers to experiment with new ideas. This requires good engineering (for example designing, implementing, and optimizing state-of-the-art AI models), writing bug-free machine learning code (surprisingly difficult!), and acquiring deep knowledge of the performance of supercomputers. In all the projects this role pursues, the ultimate goal is to push the field forward. We’re looking for people who love optimizing performance, understanding distributed systems, and who cannot stand having bugs in their code. Since our training framework is used for large runs with massive numbers of GPUs, performance improvements here will have a large impact. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Apply the latest techniques in our internal training framework to achieve impressive hardware efficiency for our training runs - Profile and optimize our training framework - Work with researchers to enable them to develop the next generation of models You might thrive in this role if you: - Have run small scale ML experiments - Love figuring out how systems work and continuously come up with ideas for how to make them faster while minimizing complexity and maintenance burden - Have strong software engineering skills and are proficient in Python About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-ba

About the Team The Developer Experience team at OpenAI has a singular focus: empowering developers globally. Our mission is to provide every developer and startup on the planet with the most delightful and seamless experience to integrate AI into their applications and products. We ensure developers have the tools, resources, and support they need to unlock AI’s full potential. We create inspiring demos, developer tools, sample applications, and technical content that show developers how to build with Codex and frontier models like GPT-5.5 and GPT-Image-2 to create powerful agents and AI-native applications. We collaborate closely with product, engineering, research, and GTM teams to ensure the developer journey, from onboarding with Codex to first API call to production deployment, is seamless, effective, and delightful. About the Role As a Developer Experience Engineer, you will create compelling technical content, developer tools, and sample applications designed to inspire developers and enable them to succeed with Codex and OpenAI’s APIs and products for developers. You will engage with developers and technical founders, demonstrating best practices and building innovative applications powered by frontier models, multimodal capabilities, and tools like Codex. We’re looking for people who combine strong technical skills, creativity, and a passion for engaging with and empowering developers. In this role, you will: - Develop demos and sample applications that showcase best practices for building with Codex, frontier models, multimodal capabilities, and agents. - Create high-quality technical content, including tutorials, blog posts, videos, and code samples, to educate and inspire the developer community about our models, APIs, and Codex. - Actively engage with and foster a vibrant Singapore and global developer ecosystem around OpenAI's platform and products. - Represent OpenAI at developer events and online, serving as a knowledgeable and approachable advocate for developers. - Gather and synthesize developer feedback to inform and improve our product roadmap. - Collaborate cross-functionally with product, engineering, and marketing teams to drive adoption and success across OpenAI's developer products, including Codex and our APIs. - Contribute directly to improving and refining OpenAI's developer products, interfaces, and surfaces. - Own challenges end-to-end, proactively closing gaps and developing new skills to solve complex problems. - Travel across APAC up to ~30% of the time to meet developers, support events, and build local communities. You might thrive in this role if you: - Are passionate about crafting exceptional developer experiences and creating inspirational technical content and projects. - Bring a robust full-stack engineering background with demonstrated experience building innovative applications using AI and large language models (LLMs). - Mandarin language skills as the role will also cover clients and communities that are Mandarin-speaking. - Have strong user empathy and care deeply about delivering experiences developers truly appreciate. - Have a proven track record of successfully creating engaging technical content, compelling demos, or innovative developer tooling that accelerates technology adoption. - Find joy in coding, continuously shipping high-quality, impactful software. - Excel in dynamic environments characterized by rapidly evolving priorities, ambiguity, and competing deadlines. - Are an exceptional collaborator who thrives working cross-functionally and enjoys partnering with diverse teams. - Maintain a genuine commitment to AI ethics and safety, strongly aligning with OpenAI's responsible AI development principles. - Stay deeply current on OpenAI's latest developer products and offerings, including Codex, APIs, and frontier models, and translate that fluency into useful demos, content, and developer guidance. About OpenAI OpenAI is an AI research and deployment company dedicated to

About the Team The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. About the Role As a member of Agent Post-Training, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. In this role, you might - Design and run experiments that improve agentic model behavior across coding, tool use, function calling, computer use, multi-agent collaboration, long-horizon tasks, factuality, instruction following, and calibrated reasoning. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex, API/platform, and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. You might thrive in this role if you - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthe

ABOUT THE TEAM Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security https://openai.com/index/updating-our-preparedness-framework/ that could scale to an extreme level of severity. Our work involves: 1. Measurement. Monitoring and predicting the evolving capabilities of frontier AI systems. 2. Mitigation. Keeping misuse safeguards, alignment tools, and security measures on track to adequately address extreme threats that might arise in the future. 3. Coordination. Setting mitigation targets by maintaining OpenAI’s preparedness framework https://openai.com/index/updating-our-preparedness-framework/, and partnering with other staff to achieve these targets. This is urgent, fast-paced work that has far-reaching implications for the company and for society. ABOUT THE ROLE This role leads the Automated Red Teaming (ART) effort: building scalable, research-driven systems that continuously uncover failure modes in our models and safeguards, and translate those findings into actionable, production-facing improvements. The goal is to reduce expected harm by finding the highest-leverage, least-covered weaknesses early and reliably. IN THIS ROLE, YOU'LL: - Own the research and technical direction for automated red teaming across catastrophic risk areas, with an initial emphasis on: - Automated classifier jailbreak discovery (cyber and bio). - Automated bio threat-development elicitation (worst-feasible planning uplift). - CoT monitoring evasion probing (and adjacent loss-of-control evaluations). - Partner closely with: - Vertical risk teams (Cyber, Bio, Loss of Control) to define threat models, prioritize targets, and land mitigations. - The Classifiers team to turn discovered attacks into training data, evals, and measurable robustness gains. - Product / Engineering / Safety stakeholders to ensure ART outputs are operationally useful. YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Feel a strong pull toward AI safety, and you’re motivated by reducing real-world catastrophic risk (not just publishing cool results). - Love breaking systems (responsibly) — you get energy from finding weird, high-severity failure modes and turning them into concrete fixes. - Have strong applied research instincts, especially around evaluations: you’re good at designing experiments that are reproducible, interpretable, and hard to fool. - Bring hands-on experience with LLMs and agents, including multi-turn behaviors, tool use, and the ways models adapt to constraints. - Are comfortable building scalable automation, not just prototypes — you can turn red-teaming ideas into pipelines that run continuously and produce high-signal outputs. - Have solid software engineering fundamentals (data structures, algorithms, testing discipline) and you can work effectively in a production-adjacent environment. - Think in threat models and incentives, and you naturally ask “what would an attacker do next?” or “how would this fail under pressure?” - Can translate messy findings into action, communicating clearly with researchers, engineers, product, and policy — and driving alignment on what to fix first. - Care about efficiency and prioritization, and you’re happy to say “no” to low-leverage work to focus on what moves the risk needle. - Nice to have: - Experience in adversarial ML, security research / red teaming, abuse prevention systems, or large-scale eval infrastructure. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportun

ABOUT THE TEAM OpenAI's Training team is responsible for producing the large language models that power our research, our products, and ultimately bring us closer to AGI. Achieving this goal requires combining deep research into improving our current architecture and optimization techniques, alongside long-term bets aimed at improving the efficiency and capability of future generations of models. We are responsible for integrating these techniques and producing model artifacts used by the rest of the company, and ensuring that these models are world-class in every respect. ABOUT THE ROLE As a member of the training team, you will push the frontier of LLM development for OpenAI's flagship models, enhancing intelligence, efficiency, and adding new capabilities. Relevant interests may include areas such as architecture design, long-context and efficient attention, optimization and the science of scaling. Ideal candidates have a deep understanding of LLM architectures, a sophisticated understanding of model inference, and a hands-on empirical approach. A good fit for this role will be equally happy coming up with a creative breakthrough, investing in strengthening a baseline, designing an eval, debugging a thorny regression, or tracking down a bottleneck. This role is based in London. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. IN THIS ROLE, YOU WILL: - Design, prototype and scale up new architectures to improve model intelligence - Execute and analyze experiments autonomously and collaboratively - Study, debug, and optimize both model performance and computational performance - Contribute to training and inference infrastructure YOU MIGHT THRIVE IN THIS ROLE IF YOU: - Have experience landing contributions to major LLM training runs - Can thoroughly evaluate and improve deep learning architectures in a self-directed fashion - Are motivated by safely deploying LLMs in the real world - Are well-versed in the state of the art transformer modifications for efficiency WORKPLACE & LOCATION: This role is based in our London office, and we aren’t considering applications to work remotely at this time. If you're joining us in person, we offer relocation support and follow a hybrid schedule: three days a week in the office, with the option to work from home on Thursdays and Fridays. Our offices are set up for focus and connection—with adjustable desks, phone booths, conference rooms, stocked kitchens, and cozy spots to unwind or catch up with teammates. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adv

ABOUT THE TEAM The Agent Post-Training team creates the frontier agents OpenAI ships to the world. We are training the models behind our agents in Codex, ChatGPT, the API, and other frontier products: persistent, proactive intelligence that can operate computers, collaborate with people and other agents, and expand what people and organizations can imagine, attempt, and achieve. We define what the next generation of agents should be able to do, build the training signal that teaches those abilities, and run the experiments that make them real. Our work spans coding, tool use, computer use, multi-agent coordination, long-horizon execution, factuality, instruction following, calibrated reasoning, and taste. Our team is where new model capabilities get made. We build the data, environments, graders, training methods, and feedback loops that shape what OpenAI's next agents can do, then carry those capabilities through major training runs and into the products people use. ABOUT THE ROLE As a member of Agent Post-Training, Connectors, you will teach models how to interface with the top professional software using code. You will help train agents to use code, APIs, tools, and structured integrations to operate across applications like Slack, Google Workspace, GitHub, Notion, Linear, Salesforce, and other core systems of work. You will help enable models to take useful actions across a user’s digital context: finding information, updating systems, coordinating work, generating artifacts, and completing multi-step workflows through the tools teams already use. You will train models to be supercharged by the world’s most important productivity and enterprise software, turning connected tools into a powerful action surface for our agents. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measure whether it worked, and ship improvements into products used by real people. This is a high-agency role for people who want their work to land directly in frontier models. IN THIS ROLE, YOU MIGHT - Design and run experiments that improve agentic model behavior for complex software and plugins.. - Own end-to-end improvements to the post-training stack, including RL, data pipelines, graders, reward signals, evals, diagnostics, and model-behavior analysis. - Build evals and environments that expose the next set of model failures, then turn those failures into training data, product fixes, or new research directions. - Partner with Codex and ChatGPT product teams to understand what users need and translate product signal into model improvements. - Work on early-training and alignment interventions, including data mixtures, objectives, synthetic data, and eval loops that shape downstream agent behavior. - Help decide which integrations, capabilities, and fixes are ready for inclusion in major model runs. - Improve the machinery for large-scale training and launch: experiment velocity, reliability, observability, reproducibility, cost, latency, and production readiness. - Take on cross-functional projects that touch model training, product infrastructure, and the production agent harness, such as multi-agent systems or training directly against production-like environments. - Debug hard failures in shipped or near-shipped models and turn messy qualitative behavior into concrete hypotheses, experiments, and fixes. YOU MIGHT THRIVE IN THIS ROLE IF YOU - Have strong technical fundamentals in machine learning, software engineering, systems, statistics, or a related field, and can learn quickly across the parts you have not worked in before. - Have hands-on experience with LLMs, RL, RLHF/RLAIF, post-training, evals, graders, synthetic data, model training, coding agents, tool-using agents, or production ML systems. - Are excited by open-ended problems where the path is unclear, the signal is noisy, and the right answer requires both research taste and

About the Team The OpenAI Robotics team is focused on unlocking general-purpose robotics and pushing towards AGI-level intelligence in dynamic, real-world settings. Working across the entire model stack, we integrate cutting-edge hardware and software to explore a broad range of robotic form factors. We strive to seamlessly blend high-level AI capabilities with the constraints of physical systems to improve peoples’ lives. About the Role As a Software Engineer, Distributed Data Systems, you will design and scale the infrastructure that powers large-scale multimodal training and evaluation at OpenAI. You’ll manage distributed data pipelines, collaborate closely with researchers to translate requirements into robust systems, and harden pipelines that serve as the backbone for OpenAI’s rapid iteration cycles. We’re looking for engineers who are detail-oriented, have strong experience with distributed systems, and excel at building reliable infrastructure in high-stakes environments. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: - Design, build, and maintain data infrastructure systems such as distributed compute, data orchestration, distributed storage, streaming infrastructure, machine learning infrastructure while ensuring scalability, reliability, and security. - Ensure our data platform can scale by orders of magnitude while remaining reliable and efficient - Partner with researchers to deeply understand requirements and translate them into production-ready systems. - Harden, optimize, and maintain critical data infrastructure systems that power multimodal training and evaluation. You might thrive in this role if you: - Have strong experience with distributed systems and large-scale infrastructure with a strong interest in data. - Are detail-oriented and bring rigor to building and maintaining reliable systems. - Demonstrate excellent software engineering fundamentals and organizational skills. - Are comfortable with ambiguity and rapid change About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf. Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information.

About the Team OpenAI’s mission is to build safe artificial general intelligence (AGI) that benefits all of humanity. Achieving this requires bringing the world’s most exceptional talent under one roof to push the boundaries of what’s possible. Our Research Recruiting team plays a critical role in this effort. We are an embedded part of the research organization, working side by side with our research staff to deeply understand evolving priorities, build trust, and strategically shape the future of OpenAI’s talent. About the Role You will own and execute long-term talent strategies to identify, engage, and recruit many of the world’s leading and emerging AI researchers, research engineers, and technical scientists working at the frontier of machine learning. This is not a traditional execution-focused recruiting role. You will operate as a strategic partner to OpenAI’s research staff, helping define hiring priorities, shape search strategy, influence candidate evaluation, and guide hiring decisions that directly impact the direction and quality of our frontier-model research and fulfillment of our mission. In this role, you will: - Partner directly with research and technical staff to define hiring priorities, shape search strategies, and anticipate future talent needs as technical roadmaps evolve. - Proactively identify and cultivate exceptional AI/ML research talent across industry, academia, and emerging labs, often before formal hiring needs exist. - Use market insights and candidate signals to influence hiring decisions, leveling, and compensation strategy for highly specialized research roles. - Serve as a trusted advisor throughout candidate evaluation and closing — helping leaders calibrate for research excellence, long-term potential, and organizational fit. - Collaborate closely with your sourcing partner to execute complex, high-impact searches in ambiguous or rapidly evolving technical domains. You might thrive in this role if you: - Significant experience recruiting within highly technical or specialized environments. - Deep interest in AI research and a desire to engage directly with global research communities. - Experience recruiting within highly technical or specialized environments such as ML/AI, distributed systems, infrastructure, scientific computing, or quantitative research. - Track record of leading complex, ambiguous technical searches from early talent mapping through close. - Experience navigating high-stakes negotiations with senior technical or research candidates. - Comfort operating in fast-moving environments where hiring priorities and role definitions may evolve over time. Workplace & Location This role is based in our London office and we aren’t considering remote applications at this time. We use a hybrid work model of 3 days in the office with optional work from home on Thursdays and Fridays. We also offer relocation assistance to new employees. Our open-plan offices have height-adjustable desks, conference rooms, phone booths, well-stocked kitchens full of snacks and drinks, three in-house prepared meals daily, outdoor space for working and socializing, wellness rooms, private bike storage, and more. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional informat