Decision Scientist in United States

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 Future of Computing Research team is an Applied Research team within the Consumer Devices group focused on developing new methods and models as we advance forward in our mission of building AGI that benefits all of humanity. As a Software Engineer on the Future of Computing Research team, you will work together with both the best ML researchers in the world and the greatest design talent of our generation to push the frontier of model capabilities. About the Role We are looking for a Software Engineer to join our team to build tools and services that enable AI research, evaluation, and data generation workflows. The best work in this role will start with an ambiguous design question and turn it into working research systems. You will work closely with researchers, designers, and engineers to build the evaluation systems, synthetic data generation pipelines, review tools, and supporting platform services. The goal is to make these workflows easier to create, run, and trust without requiring bespoke engineering support for each new design concept. You will help ensure that research artifacts have a clear lifecycle, runs are reproducible and observable, and results provide useful evidence for product and model-training decisions while the underlying systems remain reliable and reusable. 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: Build web applications, APIs, data models, and backend services for AI research workflows. Build tools to author and manage evaluation tasks, rubrics, graders, suites, and rollout configurations, including workflows for publishing, versioning, auditing, and sharing research artifacts. Automate evaluation runs and generate useful reports for design, research, and engineering teams. Support synthetic data generation workflows for multimodal and conversational research, including tools that comb

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 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 Controls Network Engineer, you will design, validate, and scale the controls and OT network architectures that support high-density AI data centers. You will work across controls systems, OT infrastructure, telemetry, commissioning, deployment, and operations, partnering with mechanical, electrical, IT/networking, security, and external delivery teams. About the Role We are seeking a mid to senior OT Network Engineer with a strong controls systems background to lead the design and operation of resilient, secure, and scalable OT network architectures for high-density AI data centers. This role translates compute, power, cooling, and operational requirements into practical OT network designs, evaluates vendor solutions, and drives technical decisions across controls infrastructure, telemetry, commissioning, and operations. The ideal candidate has strong hands-on experience in mission-critical OT environments, including industrial networking, virtualized infrastructure, and OT network operations, with expertise in routing, switching, segmentation, firewall policy, time synchronization, monitoring, and network lifecycle support. Key Responsibilities Define controls, automation, and OT network requirements for AI data center campuses. Develop reference architectures, engineering standards, and reusable design templates. Review and develop basis-of-design and functional design documents, including OT network diagrams, IP/VLAN schemes, telemetry architectures, data flow diagrams, and commissioning requirements. Design OT and infrastructure network architectures, including physical topology, logical topology, IP addressing, subnetting, VLA

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 multimoda

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 OpenAI is looking for an experienced Performance Engineer to help us scale the performance, reliability, and efficiency of our systems. In this role, you'll apply deep technical expertise to optimize infrastructure and application-level performance across mission-critical products like ChatGPT and our developer API. You’ll work cross-functionally with teams building core services, training models, and developing real-time user experiences to push our latency, throughput, and cost-efficiency to the next level. We are looking for engineers who thrive in ambiguous environments, value deep systems understanding, and are motivated by delivering measurable impact. This is a highly technical, individual contributor role focused on root-cause analysis, profiling, instrumentation, and architecture-level performance improvements across our stack. In this role, you will: Analyze and optimize performance across application, middleware, runtime, and infrastructure layers—networking, storage, Python runtime, GPU utilization, and beyond. Develop tooling and metrics that provide deep observability into system performance. Collaborate closely with infra, platform, training, and product teams to identify key performance goals and drive systemic improvements. Influence architecture and design decisions to prioritize latency, throughput, and efficiency at scale. Lead investigations into high-impact performance regressions or scalability issues in production. Drive performance testing strategies and help define SLAs/SLOs around latency and throughput for critical systems. You might thrive in this role if you: Have 7+ years of experience in software engineering with a strong tr

About the Team Our team turns OpenAI’s latest model capabilities into polished, trusted products for consumers and developers. We build the end-to-end experiences including product surfaces, platform layers, and developer workflows that make cutting-edge AI accessible, useful, and dependable at scale. OpenAI’s Financial Engineering (FinEng) team powers how revenue flows through our products - pricing and packaging, checkout, payments, subscriptions, and the financial infrastructure behind them. We partner closely with Engineering, Data Science, Risk, Finance, and Go-to-Market to make paying for OpenAI products seamless, reliable, and efficient worldwide. We pair rapid innovation with a rigorous approach to responsible deployment. Safety and trust are built into how we design, ship, and learn from real-world usage, so these tools deliver meaningful value while aligning with OpenAI’s mission. About the Role We are seeking an experienced Product Manager to scale the product efforts and technical strategy within our Financial Engineering team. The ideal candidate has prior experience in billing, finance, and accounting, ideally also building solutions for commercial users of varying sizes from small scale to enterprise. This role requires close collaboration with our product, finance, operations, and engineering teams. This position is based in San Francisco, CA. We utilize a hybrid work model with 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Develop a strategy and roadmap to efficiently scale the billing operations and customer experience behind OpenAI’s growing product portfolio Identify and execute opportunities to improve the order-to-cash processing for OpenAI’s largest and most strategic customers Build AI powered tooling for key partner teams such as Finance and User Operations to drive better decisions and business outcomes Collaborate with other product teams to defining OpenAI’s evolving monetization s

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 h

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in San Francisco. W

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 mak

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 desig

About the team OpenAI’s Forward Deployed Engineering (FDE) team turns research breakthroughs into production-grade systems. We embed deeply with customers to solve high-leverage problems and act as the delivery engine for our most complex large-scale engagements. We move quickly from prototype to production and surface reusable patterns that shape our platform. We operate at the intersection of deployment and development – working closely with OpenAI Research, Product and Partnerships. About the Role As a Technical Deployment Lead (TDL), you will define how OpenAI delivers complex systems to customers. You will own how they are built, shipped, and adopted. You’ll translate business outcomes into a technical plan, run day-to-day execution across FDEs, Researchers, and Customer Engineers, and partner with customer teams to ensure delivery supports their goals. You will own delivery end-to-end: embedding with customers to map workflows and success criteria, ensuring components ship on time, and leading readiness and change management for adoption. You’ll track progress, manage dependencies, make sequencing decisions, and drive 0→1 prototypes through MVP and scale. You will also share field insights with Product and Research to guide roadmap and priorities. Success will be measured first and foremost by impact - deployments that deliver measurable value against customer goals, drive adoption, and become critical to their workflows. Additional measures of success include delivery reliability (milestones hit, low reopen/churn), operating leverage (patterns reused across deployments), judgment under pressure, and product impact (field signal that shifts roadmaps/architectures). This is a high-trust, high-autonomy role. Success requires deep technical project management expertise, extreme ownership of outcomes, and an ability to immerse in customer workflows and partner with customer teams to solve complex engineering problems at pace. This role is based in NYC. We use a hy

About the Team The Stargate team is responsible for building the physical infrastructure that powers large-scale AI systems. We design and deliver next-generation data centers optimized for dense compute clusters, advanced networking, and rapidly evolving hardware platforms. This work sits at the intersection of hardware engineering, systems architecture, and infrastructure execution—translating cutting-edge compute roadmaps into scalable, production-ready environments. Our teams partner across silicon vendors, server and storage OEMs, networking teams, and data center engineering organizations to bring new capacity online quickly, reliably, and at global scale. About the Role We are seeking a CPU & Storage Technical Lead to define and drive the server compute and storage architecture strategy for Stargate infrastructure. In this role, you will own technical direction across CPU platforms, memory configurations, local and disaggregated storage systems, and their integration into large-scale AI clusters. You will evaluate vendor roadmaps, lead platform tradeoff decisions, and ensure compute and storage systems are optimized for training, inference, and supporting services. You will work cross-functionally with hardware engineering, performance modeling, networking, supply chain, and deployment teams, as well as external partners such as AMD, Intel, OEMs, ODMs, and storage vendors. This is a highly strategic role for someone who can operate deeply at the component level while also driving long-range infrastructure decisions. Key Responsibilities Own CPU and storage technical strategy for Stargate compute infrastructure across current and future generations. Evaluate CPU platforms across performance, efficiency, memory bandwidth, PCIe topology, cost, and roadmap alignment. Define storage architectures for AI environments, including boot media, local NVMe, shared storage, caching tiers, metadata services, and high-performance data pipelines. Drive server platform de

About the Team Safety Systems manages the complete lifecycle of safety efforts for OpenAI’s frontier models, ensuring our models are deployed responsibly and have a positive impact on society. Our work spans diverse research and engineering initiatives—from system-level safeguards and model training to evaluation and red-teaming—all aimed at mitigating misuse and maintaining our high bar for safety. We lead OpenAI's commitment to developing and deploying safe Artificial General Intelligence (AGI), fostering a culture of trust, responsibility, and transparency. Our goal is to continuously learn from deployments, distribute AI’s benefits widely, and ensure that powerful tools remain aligned with human values and safety considerations. About the Role The Safety Measurement Product Manager owns OpenAI's approach to measuring harm and safeguard efficacy in production, including driving the strategy for our suite of safety measurement platforms and products used across the company. You will partner closely with our safety research and engineering teams to determine what we measure, where we measure it, and how we measure it, feeding those insights directly into critical leadership decisions and back into our safety work. You will also represent the company's topline safety metric as well as prioritize incoming requests from partner teams to expand our safety measurement platform to more use cases. This position is based in San Francisco, CA, with relocation assistance available. In this role, you will: Partner closely with data science, research, engineering, policy teams, and other stakeholders to craft a vision for understanding safety outcomes and prevalence on our platforms. Define strategic priorities and product roadmaps focused on improving safety measurement approaches will scaling our measurement platform to more use cases, products, and cross-functional team needs. Establish repeatable processes to integrate cutting-edge AI safety research into OpenAI’s safety m

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 E