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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 resea

About the team Preparedness is a critical Safety Research team at OpenAI, which is focused on mitigating AI threats to global security that could scale to an extreme level of severity. Our work involves: Measurement. Monitoring and predicting the evolving 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 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

About the Team Our Inference team brings OpenAI’s most capable research and technology to the world through our products. We empower consumers, enterprise and developers alike to use and access our start-of-the-art AI models, allowing them to do things that they’ve never been able to before. We focus on performant and efficient model inference, as well as accelerating research progression via model inference. About the Role We are looking for an engineer who wants to take the world's largest and most capable AI models and optimize them for use in a high-volume, low-latency, and high-availability production and research environment. In this role, you will: Work alongside machine learning researchers, engineers, and product managers to bring our latest technologies into production. Work alongside researchers to enable advanced research through awesome engineering. Introduce new techniques, tools, and architecture that improve the performance, latency, throughput, and efficiency of our model inference stack. Build tools to give us visibility into our bottlenecks and sources of instability and then design and implement solutions to address the highest priority issues. Optimize our code and fleet of Azure VMs to utilize every FLOP and every GB of GPU RAM of our hardware. You might thrive in this role if you: Have an understanding of modern ML architectures and an intuition for how to optimize their performance, particularly for inference. Own problems end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done. Have at least 5 years of professional software engineering experience. Have or can quickly gain familiarity with PyTorch, NVidia GPUs and the software stacks that optimize them (e.g. NCCL, CUDA), as well as HPC technologies such as InfiniBand, MPI, NVLink, etc. Have experience architecting, building, observing, and debugging production distributed systems. Bonus point if worked on performance-critical distributed systems. Have need

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 Sales team has a unique mission to help customers understand the deep impact that highly capable AI models can bring to their business and users. This role is a mixture of technical understanding, vision, partnership, and value-driven strategy. You’ll be a key driver of opportunities through the entire sales cycle, from pipeline generation to closure. You’ll work with researchers, engineers, and solution strategists to help customers evolve their industry with 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'll: Manage a portfolio of customer accounts, developing and executing strategies for a comprehensive account plan Support your customer accounts from initial engagement to successful deployment, expansion, and through to renewal Develop new and existing accounts through pipeline generation, discovery, evaluation, and successful adoption Partner with solutions and research engineering to build and execute complex customer programs and projects Own a revenue target Manage revenue forecasts Analyze key account metrics to create reports and provide insights to internal and external stakeholders Closely monitor the industry landscape (people, competitors, partners, etc.) to contribute to product roadmap and

About the team OpenAI’s Forward Deployed Engineering team partners with customers to turn research breakthroughs into production systems. We operate at the intersection of customer delivery and core platform development. About the Role We are looking for customer-focused software engineers to build effective custom software that leverages OpenAI’s APIs to solve real customer problems. As an FDSWE, you will work with our customers and OpenAI Forward Deployed Engineers to design and implement scalable solutions that solve their most difficult problems. You will design abstractions to solve customer problems, and then use them to scale our speed and quality of delivery across all Forward Deployed engagements. You will collaborate closely with Sales, Solutions Engineering, Solutions Architects, and Customer Success Managers who work on the same account. You will also work with our Research and Applied Product and Engineering teams to provide insightful customer feedback. This role is based in San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required. In this role, you will: Embed deeply with strategic customers to understand their business challenges and technical requirements in detail. Design, architect, and develop full-stack solutions using an experiment-driven, iterative approach. Prepare detailed scopes of work and project plans for both proof-of-concept prototypes and full production deployments. Work hands-on with customers' technical teams as a technical expert and trusted advisor, coding side-by-side to drive projects to completion on their infrastructure. Collaborate with Product, Research and Applied teams to ensure seamless customer experiences, project success and actionable product feedback Contribute to internal knowledge bases, codifying best practices and sharing insights gained from customer engagements to scale the Forward Deployed Engineering function. You’ll thrive in th

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the machine learning infrastructure that powers OpenAI’s monetization and ads systems. In this foundational role, you’ll design and develop the platform layer that enables teams to build, train, deploy, serve, monitor, and continuously improve machine learning models used across advertising and monetization products. You’ll work across the full ML lifecycle, from large-scale data pipelines and feature infrastructure to training systems, model serving, experimentation platforms, and monitoring frameworks. The systems you build will support high-throughput, low-latency advertising workloads while maintaining strict standards for reliability, privacy, security, and performance. This role sits at the intersection of machine learning systems, distributed infrastructure, and monetization, offering the opportunity to shape the core platforms that help translate model innovation into m

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 tran

About the Team Our 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 i

About the Team OpenAI’s Finance and Revenue Operations organization builds the commercial infrastructure that enables the business to scale with speed, discipline, and financial integrity. Deal Desk operates as the commercial strategy and governance function at the intersection of Sales, Partnerships, Legal, Technical Revenue, Finance, Order Management, Billing Operations, Product, and GTM Systems. We architect complex enterprise transactions, turn ambiguity into executable decisions, and create the guardrails that let the business move quickly with operational and financial discipline. As OpenAI’s enterprise business grows in scale and complexity, Deal Desk defines how novel commercial motions become durable operating capabilities. We convert precedent-setting deal decisions into repeatable policy, controls, workflows, and systems requirements. About the Role We are hiring a Strategic Deals & Commercial Architecture Lead to lead the structuring and governance of OpenAI’s most complex enterprise transactions. This is a senior individual-contributor leadership role for someone with exceptional enterprise deal judgment, operational rigor, and a builder mindset. You will serve as the commercial architect for high-stakes opportunities, translating ambiguous requirements into coherent deal structures, approval strategies, and executable quote-to-cash plans. Your work will shape more than individual transactions. You will establish decision principles and precedent, clarify tradeoffs, and turn recurring patterns into scalable guidance, controls, systems requirements, and enablement. You will own the commercial decision and governance layer that helps strategic opportunities move decisively while managing downstream risk across contracting, billing, revenue recognition, provisioning, reporting, controls, auditability, and customer experience. The right candidate can move seamlessly between advising on a single high-value transaction and improving the operating model be

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

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

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, a

About the Team The Storage Infrastructure team builds and operates the storage foundation behind OpenAI’s most demanding workloads. We work directly with research to design storage systems for rapidly evolving experiments, while also powering production at scale. We own the platform end to end: backend systems, user-facing services and APIs, and the control planes that manage how data is placed, moved, and retained over time. Our stack spans cloud and in-house object stores across very different workload profiles, from GPU-attached systems to dedicated storage hardware. We also build the federation layer that unifies these backends behind a simple interface and routes each workload to the right storage solution. About the Role You will help build the storage platform that powers OpenAI’s research and production systems. This is a hands-on infrastructure role for engineers who want to work on deeply technical systems at scale and own them in production. You’ll work across object storage, cross-region data movement, lifecycle management, and the federation layer that provides a unified interface across multiple backends. Much of our stack runs on Kubernetes, and we primarily build services in Rust. In this role, you will: Build and operate storage services that underpin OpenAI’s research infrastructure Develop object storage systems across cloud and in-house environments Build systems for cross-region data movement, replication, and recovery Design lifecycle management capabilities that keep data durable, available, and cost-effective Evolve the federation layer that unifies multiple backend systems behind a simple interface Improve performance, reliability, and operational excellence across the platform Collaborate closely with researchers and infrastructure teams to support rapidly evolving workloads You might thrive in this role if you: Have experience building or operating distributed systems in production Have worked on storage infrastructure, object stores, dist

About the Team Codex is OpenAI’s first-party developer product focused on agentic software engineering. We’re building tools that help engineers design, write, test, and ship code faster—safely and at scale. We partner tightly with research and product to translate model advances into tangible developer productivity. About the Role As a Data Scientist on Codex, you will measure and accelerate product-market fit for AI developer tools. You’ll define what “developer productivity” means for our product, run experiments on new coding models and UX, and pinpoint where the model helps or hurts across languages and tasks. Your insights will directly shape how an entire industry builds software. 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 Embed with the Codex product team to discover opportunities that improve developer outcomes and growth Design and interpret A/B tests and staged rollouts of new coding models and product features Define and operationalize metrics such as suggestion acceptance, edit distance, compile/test pass rates, task completion, latency, and session productivity Build dashboards and analyses that help the team self-serve answers to product questions (by language, framework, repo size, task type) Diagnose failure modes and partner with Research on targeted improvements (model quality signals, user feedback, evals) You might thrive in this role if you have 5+ years in a quantitative role at a developer-facing or high-growth product Fluency in SQL and Python; comfort with experiment design and causal inference Experience defining product metrics tied to user value Ability to communicate clearly with PM, Eng, and Design—and to influence product direction You could be an especially great fit if you have Strong programming background; ability to prototype, run simulations, and reason about code quality Familiarity with IDE/extensi

About the Team Our infrastructure team helps deliver OpenAI’s most capable models and products to the world by scaling infrastructure and turning demand into useful FLOPS. We collaborate across research, engineering, design, and business to turn cutting-edge AI advancements into impactful, real-world applications. Our team ensures the right compute is available—at the right time and place—to support some of the world’s most demanding workloads. We empower all of OpenAI’s products and research by scaling the infrastructure behind them. Our work makes it possible to launch new models and products reliably and at scale. About the Role As a Data Scientist on the Infra team, you will play a key role in shaping how we scale the infrastructure that powers OpenAI’s products and research. This is critical as we operate one of the largest and most advanced compute fleets in the world, supporting millions of users and businesses globally. We focus on aligning infrastructure measurement, planning, scaling, allocation, and efficiency to drive measurable impact across the company. You should expect to guide the definition of foundational datasets for infrastructure resources, develop metrics that inform key decisions, build forecasting and optimization models, and establish source of truth dashboards and analyses that enable teams to understand and improve infra usage. Most importantly, you should expect to be a core partner to engineering, research, and product teams in shaping the infrastructure that powers everything OpenAI builds. 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 foundational datasets and metrics that reflect infrastructure usage, efficiency, and scaling. Develop forecasting and optimization models to support infra planning and resource allocation. Partner with engineering, research, and product teams to shape infrast