Design Methodology in United States

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 The Technical Support team is responsible for ensuring that developers and enterprises can reliably build mission critical solutions using OpenAI models. We provide technical guidance, resolve complex issues and support customers in maximizing value and adoption from deploying our highly-capable models. We work closely with Technical Success, Product, Engineering and others to deliver the best possible experience to our customers at scale. We think from an automation-first mindset and leverage the latest in AI to scale our support operations. Join the Senior Support Engineering (SSE) team at OpenAI and help shape the future of Technical Support in the age of AI. About the Role We are looking for a Senior Support Engineer to collaborate directly with our strategic enterprise accounts and product teams, helping solve some of the most difficult problems faced by our Customers. You will be part of the best technical troubleshooting team at OpenAI, and our Customers and Engineering teams will look to you for technical guidance in addressing the most technically difficult issues in our environment. As a Senior Support Engineer, you will design and run operational processes to monitor our top strategic customers and a 24x7 response team. You’ll work closely with our Infrastructure and Engineering teams to deliver the best possible experience to customers at scale. Working directly with our most strategic Customers - You will be crucial to the success of the most innovative, disruptive, and high-scale AI solutions being built with the OpenAI API platform. The nature of this role will be low volume, high difficulty. 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: Be among the foremost technical and troubleshooting experts for our API platform at OpenAI. You are the last line of defense before the core Engineering team. Proactively iden

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 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 th

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 team brings OpenAI’s most capable technology to the world through our developer platform: the OpenAI API. As the leading AI development platform, our API is used by millions of developers and the majority of enterprises around the world, and powers the majority of AI applications that you may use on a daily basis. The platform supports everything from simple model calls to stateful, multimodal, tool-using applications through the Responses API, Agents SDK, Realtime API, and more. Our SDKs turn that fast-moving platform into reliable, idiomatic developer experiences across languages. About the Role We are looking for a software engineer to help build the official SDKs that power the OpenAI API. Currently offered in Python, Node.js, Golang, Java, and Ruby – our SDKs are some of the most popular in the world. You will help shape the developer experience for all new API features, as well as all future versions of our APIs. We’re looking for engineers who are deeply immersed in AI-native development: people who actively build with Codex and other coding agents, have developed agentic applications or developer tools, and bring strong, experience-backed opinions about OpenAI’s APIs. You’ll pair that firsthand product intuition with meticulous SDK design to improve how developers build with our platform. Prior experience building SDKs is lovely, but not absolutely necessary. In this role, you will: Define and implement the SDK experience for all new API features, as well as all future versions of our API. Build and experiment with agentic applications, developer tools, and coding-agent workflows using Codex and OpenAI’s APIs, translating firsthand experience into better SDK abstractions, API ergonomics, and developer experiences. Build and maintain our systems to make SDK maintenance and generation streamlined and automated. Contribute to our SDK strategy and roadmap, including which languages to support and what features to support. Collaborate closely w

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 Lead Robotics Safety Engineer to define and lead the product safety strategy for our robotics program. You will work closely with leadership, engineering, research, legal, and policy teams to ensure safety is integrated into our products from the earliest stages of development through deployment. This role combines product safety, regulatory strategy, systems engineering, and risk management. You will help shape how we think about safety across robotic platforms, influence product architecture and development decisions, and ensure our systems are designed to meet both current and emerging regulatory expectations. You will serve as a subject matter expert on robotics safety standards, regulatory frameworks, and safety engineering practices while helping establish the long-term safety strategy for our products and organization. This role is based in San Francisco, CA. This role will be expected to be in office 4 days per week and offer relocation assistance to new employees. In this role, you will Define and lead the product safety strategy for robotic systems across the development lifecycle. Monitor and influence emerging regulatory frameworks, industry standards, and policy developments relevant to robotics and autonomous systems. Partner with engineering teams to translate safety requirements into product architecture, design decisions, and engineering requirements. Develop and maintain system-level hazard analyses, risk assessments, and safety cases for robotic products. Establish safety requirements, verification strat

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 Our technologies support some of the most important and impactful work in the world, including our strategic and high-impact customers in the public sector. As a Forward Deployed Security Engineer (FDSecE) you will be responsible for securing these novel applications of OpenAI’s technology. We’re looking for motivated, tenacious, and curious people who will work closely with engineering teams to ensure our infrastructure deployments are highly secure against our adversaries. As an FDSecE, you will embed directly throughout the lifecycle, working on-site and being hands-on to ensure the overall security of these deployments from design to production and through ongoing operations. This role is preferred to be based in Washington DC but may consider remote work. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. Travel to and working from customer sites is required for this role. In this role, you will: Deeply embed with our most strategic public sector customers to implement and maintain robust security controls. Be a design and technical thought partner by leveraging security expertise on protective controls including access controls, authentication, encryption, network, and system security. Collaborate closely with teammates, cross-functional teams, customers, and service providers to achieve security and compliance goals. Ensure continuity of critical security and monitoring c

About the Team The Safety Systems team 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 challen

About the Team At OpenAI, we’re building the connective tissue between our mission and our people. People Innovation Labs is a fast-moving engineering team embedded in the People organization, focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we’re designing systems that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation. About the Role We’re seeking a Data Engineer to build data-intensive systems that will power People Innovation Labs’ internal products and enable the People Analytics function to do their best work. These data pipelines are crucial for our build-out of people products backed by business systems of record and for ongoing people data analytics. One example of an employee-facing product you’ll help us build is OpenHouse, which serves as a culture and communication hub and an organization-wide front door into all other aspects of People Innovation Labs’ work. OpenHouse and other products in our portfolio are built by full stack product engineers who are deeply curious about culture, recruiting and people development, and want to know everything from the business strategy and metrics down through the code that gets us there. In this role, you will work with People Innovation Labs leadership and software engineers and the People Analytics team to build the data systems that enable this work. In this role, you will: Design, build and manage people data pipelines, ensuring all data is seamlessly integrated into our Databricks warehouse. Develop canonical datasets to track key people metrics and People Innovation Labs produc

About the Team At OpenAI, we’re building the connective tissue between our mission and our people. People Innovation Labs is a fast-moving engineering team embedded in the People organization, focused on rethinking how we find and retain the best talent and empower everyone to do their best work. From recruiting to culture, we’re designing systems that give our People Team a significant edge by infusing OpenAI’s models and first-principles thinking into every aspect of our work. Our projects range from greenfield 0-1 products like OpenHouse (our internal knowledge hub) to AI-powered automations and scalable recruiting tools. We’re defining the future of work at OpenAI, creating a blueprint for how AI can supercharge productivity, culture, and innovation. About the Role We are looking for a self-starter engineer who loves building new products in an iterative and fast-moving environment. This team is for full stack product engineers who are deeply curious about culture, recruiting and people development, and want to know everything from the business strategy and metrics down through the code that gets us there. In this role, you will work with members of the People Team and leaders across the company to build software focused on HR, culture and recruiting from the ground up. You’ll also innovate on how we apply LLMs in these domains. In this role, you will: Own the full product development lifecycle for new people products end-to-end Talk to internal stakeholders to understand their problems and design solutions to address them Work with the research team to share relevant feedback and iterate on applying their latest models Collaborate with a cross-functional team of engineers, HRBPs, recruiters, researchers, product managers, designers, and people in operations to create cutting-edge products Your background might look something like: 4+ years of professional engineering experience (excluding internships) in relevant roles at tech and product-driven companies Forme

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

AI Systems Engineer - Codex Core Agents About The Team The Codex Core Agents team builds the agent harness that turns model capability into real-world action. We own the systems around the model: prompting and interpreting model outputs, executing actions safely in real environments, and feeding production experience back into better models and better agent behavior. This team sits close to research and works across the stack: harness, model interaction, inference, sandboxed execution, orchestration, evals, production reliability, and the performance envelope around tokens, latency, cost, capacity, and quality. The harness is open source and increasingly part of how models are trained and evaluated, making this one of the highest-leverage layers in Codex. About The Role We’re looking for engineers to build the AI systems that make Codex agents dependable in production. The ideal candidate is an agent-systems builder: hands-on across low-level systems and ML workflows, able to debug Codex behavior end to end across the harness, model behavior, inference/runtime stack, GPU fleet, and product surface. You’ll work with research, infrastructure, and product to design agent harness capabilities, run experiments and ablations across the model + system prompt + harness stack, build frameworks for assessing production agent performance, and turn messy failures into durable improvements. What You’ll Do Design and build the core agent harness and execution loop that lets Codex agents interpret model outputs, use tools, execute code, and complete long-horizon tasks safely. Build sandboxing, isolation, orchestration, state, and workflow infrastructure for agents operating in real development environments. Develop evaluation, experimentation, and debugging systems that distinguish harness issues, model behavior, inference/runtime issues, and product failures. Run ablations across prompts, model-facing interfaces, context construction, tool-use strategies, and harness behavior to

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 m

About the Team The IT and Security organization builds the systems, data foundations, and automation that help OpenAI operate securely and reliably at scale. We support critical domains across identity, access, infrastructure security, enterprise systems, and internal productivity. As OpenAI grows, audit readiness and control assurance increasingly depend on reliable data: accurate system inventories, access populations, change records, configuration state, exception signals, and evidence generated directly from source systems. Our goal is to move beyond manual evidence collection and build scalable data products, automated validation, and continuous control monitoring that make security and IT controls measurable, repeatable, and defensible. About the Role We are looking for an IT Controls Data Engineer to build the data infrastructure that powers audit readiness, IT controls, evidence automation, and continuous control monitoring. In this role, you will design and maintain the pipelines, datasets, models, validation logic, dashboards, and evidence exports that make IT controls measurable, repeatable, and defensible. You will work across Security, IT, Infrastructure, Engineering, Finance Risk Management, and auditors to turn complex system behavior into reliable control data products. This is a technical builder role. The ideal candidate is strong in data engineering and analytics engineering, comfortable working with enterprise and security system data, and able to explain data lineage, source-system behavior, and control logic clearly to technical and audit stakeholders. You’ll be responsible for Building reliable data pipelines, models, and datasets for IT controls, including access, identity, configuration, change, ticketing, exception, and evidence data. Creating data quality, lineage, reconciliation, and completeness checks that make control data defensible for SOX and other audit use cases. Designing automated evidence generation workflows that produce compl