High Speed Ai Interconnect Signal Integrity Engineer in United States

About the Team OpenAI's Human Data Team creates custom data solutions driving groundbreaking research. Our work enhances and evaluates our flagship models and products like ChatGPT, GPT-5, and Sora, and contributes to safety initiatives through collaboration with our Preparedness and Safety Systems teams. About the Role As a Research Program Manager (RPM) in the Human Data team you will partner with research and engineering to design and implement pragmatic solutions for collecting high-quality data. You will be a key interface between our research roadmap, external vendors, AI trainers, and the Human Data engineering team. This role is based in our San Francisco HQ. In this role, you will: Collaborate with Research: Partner with researchers to scope data collection needs, define success metrics, and establish quality measurement frameworks. Design & Execute Data Collection Campaigns: Translate research needs into actionable plans and accelerate execution by leveraging existing tooling and iterating to reach the desired outcome. In many cases, you will need to implement scrappy new solutions while partnering with engineering to design robust/scalable solutions. Unblock Yourself: You must be deeply uncomfortable with the idea of sitting around waiting for external dependencies, and have the technical acumen and drive to figure out how to achieve at least partial success in the interim. Optimize Systems & Processes: Build and optimize dashboards to track campaign performance, leveraging SQL and Python for data analysis and actionable insights. Drive Technical Roadmaps: Collaborate with engineers to enhance data platforms, resolve blockers, and ensure security best practices such as access management. Scale Your Impact : Advise and empower program managers and vendors to drive day-to-day execution so that you can focus on addressing high priority opportunities. You might thrive in this role if you: Are proficient in SQL and Python for data analysis, including q

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 obse

About the Team 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 We’re seeking Software Engineers who can solve complex, high-impact problems across our stack. In this role, you’ll join a nimble team driving the deployment of OpenAI’s technology into new environments and infrastructure that power critical missions in the public sector. You’ll work cross-functionally with product, security, and compliance teams to build the functionality needed to deliver a scalable, reliable platform. You’ll also partner directly with customers to design and build new products and features that create real-world impact. From launching net-new capabilities to optimizing how we serve inference in unique, high-stakes environments, this role offers both breadth and technical depth—giving you the opportunity to shape the future of OpenAI’s technology where it matters most. This role is based in Washington D.C., San Francisco, CA or Seattle, WA. Occasional travel to customer sites is required for this role. In this role, you will: Own the development of new customer-facing ChatGPT and OpenAI API features end-to-end, both on-premises and in the cloud, for our public sector customers. Partner and directly embed with teams across the business, including engineering, security, and compliance, to enable our products to work within the unique constraints of new environments. Talk to users to understand their problems and design solutions to address them Work with the research team to get relevant feedback and iterate on their latest models, developing solutions specific for public sector customers at both the model & data

About the Team Training Runtime builds the distributed systems that power OpenAI's largest model training runs - most recently GPT-5.5! The Data Movement area owns the infrastructure that keeps training jobs supplied with the right data at the right time, and keeps model state moving safely and efficiently across large clusters. Our work spans machine learning systems, distributed storage, high-throughput data loading, reliability engineering, and developer experience. Success means researchers can move quickly while training runs remain fast, reproducible, debuggable, and resilient at scale. About the Role We are looking for a deeply hands-on Technical Lead Manager to own datasets throughout our training infrastructure. This person will set the direction for how training jobs read data: the APIs, storage contracts, versioning model, benchmarks, debugging tools, and reliability guarantees that make data access consistent across current and future training frameworks. You will begin as the primary technical owner for dataset reads, working directly in the code while aligning researchers, training framework owners, storage teams, and infrastructure partners around a durable platform. The problem is deceptively hard at frontier scale: make enormous, heterogeneous datasets easy to consume, correct across distributed workers, observable when something goes wrong, and flexible enough to support pretraining, reinforcement learning, and multimodal training. In this role, you will Design and build a unified dataset read platform for multiple current and future training frameworks. Define dataset APIs, storage-format expectations, registration/versioning, and migration paths that make data access reproducible and maintainable. Build reliability into the read path, including stateful iteration, caching, fast restart, recovery, and clear operational contracts. Build terminal and web-based visualizers that let teams inspect text, multimodal, and reinforcement learning data late

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 System Software Engineer to join our First-Party Hardware team. In this role, you will design, build, integrate, and validate low-level system software for the manageability and health of OpenAI's first-party AI hardware systems. You will work across BMC, Linux, firmware interfaces, automation infra, boot and recovery, hardware diagnostics, telemetry, host and platform drivers, network software interfaces, and manufacturing and fleet readiness. A major part of this role is owning the acceptance path for partner-delivered system software: defining requirements, reviewing code and artifacts, reproducing builds, building tests, pushing fixes, and producing the evidence needed for launch decisions. This role is hands-on and high-ownership. You will write and review low-level software, debug issues across hardware and software boundaries, build infra and automation to test and manage devices in lab, guide partner deliverables, build validation evidence, and help carry platforms from bring-up through production deployment. Location: San Francisco, CA (Hybrid: 3 days/week onsite) Relocation assistance available. In this role, you will: Design, develop, and maintain low-level firmware and system software for first-party AI hardware manageability, including BMC software, Redfish services, gNMI telemetry, firmware update and recovery flows, BIOS/UEFI interactions, platform drivers, and hardware diagnostics. Own integration and acceptance of partner and ve

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 infrastructu

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,

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 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 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 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 may be based in San Francisco or London, subject to team needs and location approval. In this role, you will: We are seeking research engineers and res

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 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 fr

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 OpenAI Finance ensures the organization’s financial integrity and scalability in pursuit of our mission. Our Financial Reporting team is central to delivering accurate, timely, and GAAP-compliant financial information to internal and external stakeholders. We focus on building robust, scalable reporting systems and processes to support rapid organizational growth and complexity. About the Role OpenAI is hiring a Senior Manager, Financial Reporting to help build and run a best-in-class financial reporting engine in a technically complex, rapidly evolving, and high-growth environment. We are looking for a seasoned external reporting professional who pairs strong technical judgment with a roll-up-your-sleeves mindset - owning key reporting deliverables, driving rigorous tie-outs and disclosure quality, and converting ambiguity into audit-ready output. This role will collaborate closely with teams across Accounting, FP&A, Tax, Legal, and Investor Relations to improve reporting processes, streamline data flows, and elevate how financial information is communicated across stakeholders. 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: Modernize reporting workflows through AI integration — Leverage ChatGPT, Codex, and proprietary AI tools to minimize manual effort and accelerate deep analysis, while maintaining the rigorous judgment and accountability required for high-quality, audit-ready outputs. Own end-to-end financial statements and disclosures — Prepare GAAP financial statements, footnotes, and supporting schedules; maintain rollforwards, tie-outs, and internal consistency checks to ensure outputs are complete and audit-ready. Drive audit readiness and execution — Partner with external auditors to manage day-to-day audit workflow (PBC coordination, support quality, issue resolution) and keep reporting on track with minimal re

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 We are looking for a highly strategic recruiter to work closely with the Head of Research Recruiting on a small set of unusually important, high-touch searches and candidate relationships. This role will focus on exceptional talent who does not move through a standard recruiting process: highly visible researchers, technical leaders, operators, and other special-interest candidates where timing, discretion, market intelligence, and tailored engagement matter as much as process execution. This is not a conventional req-based recruiting role. You will help identify where the market is moving, develop intelligence on top talent and competitor activity, translate that intelligence into action, and orchestrate bespoke recruiting strategies for candidates who require a more nuanced path into OpenAI. You should be able to translate these signals and states into clear, actionable advice for leaders and then make it happen. In this role, you will: Partner directly with the Head of Research Recruiting and research leadership team to define priority talent targets and shape bespoke engagement strategies. Build and maintain deep market intelligence across frontier AI, research, engineering, and adjacent talent ecosystems, including competitor movement, candidate motivations, and relationship context. Proactively identify, map, and cultivate exceptional high-profile talent before there is a formal or standard hiring process attached. Translate weak signa