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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 The Hardware Health and Observability team owns the end-to-end health lifecycle of OpenAI’s global compute fleet. Our mission is to maximize healthy, usable compute across accelerator vendors, generations, cloud providers, and regions through reliable health signals, automated remediation, and scalable operational tooling. We build the systems that observe, detect, remediate, and verify hardware issues across GPUs, CPUs, networking, and platform infrastructure, enabling frontier model training and inference workloads to run reliably at hyperscale. We are the last line of defense for the success of OAI’s production and research workloads. About the Role On the Hardware Health and Observability team, you’ll build critical infrastructure that keeps OpenAI’s largest compute clusters healthy and operational at scale. Even small numbers of unhealthy systems can impact large-scale training and inference workloads. This team focuses on minimizing downtime, improving fleet efficiency, and ensuring compute resources remain continuously available to researchers and product teams. Engineers on this team own problems end-to-end, from defining health signals and debugging failures to building automated remediation systems that operate across millions of GPUs globally. In this role, you will: Define and maintain health signals across GPUs, CPUs, networking, and platform infrastructure. Build and evolve health checks that detect, remediate, and verify failures at scale. Ensure critical health checks execute with minimal latency to maximize workload uptime. Investigate hardware failures and system-level issues across large-scale compute environments. Own node lifecycle workflows including drain, quarantine, repair, RMA, and return-to-service processes. Build automation and tooling that enables global cluster management with minimal manual intervention. Partner with workload, reliability, and provider teams to integrate health signals into training and inference system

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 Frontier Systems Foundations, part of Compute Foundations at OpenAI, builds the systems software foundation that turns new compute infrastructure into reliable, usable capacity for frontier model training. Our mission is to make some of the world's largest GPU clusters work reliably for frontier training. We bring new platforms and clusters online, safely maintain installed fleets, and partner with hardware, infrastructure, and research teams to resolve the system-level issues that keep jobs from running. That means building and maintaining the software closest to the machine: Linux and Ubuntu operating-system images, kernels and modules, drivers, packages and repositories, disks and boot configuration, firmware integration, provisioning, and system-level validation. We make these components reproducible, compatible, and safe to operate across heterogeneous fleets. About the Role We are looking for systems software engineers with deep Linux and host-systems experience to build, qualify, and maintain the operating-system foundation for OpenAI's frontier compute fleet. Relevant backgrounds include kernel and module development, Linux distribution or image engineering, package management, firmware and driver integration, disks and boot, and bare-metal provisioning. You'll work closely with hardware engineers, vendors, and infrastructure teams to bring up new platforms, integrate system components, and debug failures across firmware, disks, boot, operating systems, kernels, drivers, and workload interactions. Your work will directly influence how quickly new capacity becomes usable and how reliably large GPU fleets operate. You should be comfortable writing and maintaining production-quality systems software and automation, but we do not expect expertise across every layer. This is an opportunity to go deep on challenging systems problems while building the image, package, qualification, and recovery paths that power the next generation of frontier models

About the Team The Youth Well-Being product team is part of the Integrity pillar at OpenAI, responsible for ensuring that our state-of-the-art AI technologies are deployed in safe, age-appropriate, and beneficial ways—especially for youth and families. We work across OpenAI’s entire product surface area, from ChatGPT to future-facing tools, to architect safety and trust into the foundation of our systems. Our mission: empower families while meeting the highest standards of regulatory compliance and ethical responsibility. This work is core to OpenAI’s mission to ensure AGI benefits all of humanity. Safety, especially for the most vulnerable users, is more important to us than unfettered growth. About the Role We’re looking for a Senior Software Engineer to help architect and build the foundational systems that power family- and youth-facing experiences at scale. You’ll help define how teens and guardians engage with OpenAI products—ensuring those experiences are safe, compliant, and empowering. You’ll operate across a broad technical surface: building identity primitives, age assurance pipelines, and guardian tools that support both proactive and reactive interventions. You’ll collaborate closely with a cross-functional team of engineers, data scientists, designers, user researchers, and policy experts. This is a high-impact, 0→1 opportunity to set the standard for how families interact with generative AI. In this role, you will: Architect and implement teen and guardian experiences across OpenAI products, including ChatGPT. Build global age assurance systems that are privacy-preserving and tailored to regional compliance needs. Design and evolve our identity infrastructure to support scalable, secure, and resilient user journeys at consumer internet scale. Help define safety and well-being metrics, and continuously improve user trust through technical interventions. You might thrive in this role if you: Have built products or infrastructure for users under 18, or h

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

Join the engineering teams that bring OpenAI’s ideas safely to the world!! The Applied Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. We seek to learn from deployment and distribute the benefits of AI, while ensuring that this powerful tool is used responsibly and safely. Safety is more important to us than unfettered growth. About the Role As OpenAI continues to grow, we are looking for experienced, problem-solving engineers to ensure our systems scale. Our success depends on our ability to quickly iterate on products while also ensuring that they are performant and reliable. You will work in a deeply iterative, collaborative, fast-paced environment to bring our technology to millions of users around the world, and ensure it’s delivered with safety and reliability in mind. Successful candidates will play a crucial role in ensuring the reliability, scalability, and performance of our systems as we continue to expand. As a reliability expert, you will be at the forefront of maintaining and enhancing the stability, scalability, and performance of our rapidly evolving infrastructure. You will work closely with cross-functional teams, including software engineers, product managers, and data scientists, to build and maintain resilient systems that can handle our growing user base and workload. In this role, you will: Design and implement solutions to ensure the scalability of our infrastructure to meet rapidly increasing demands. Build and maintain the load, chaos and synthetic testing software leveraged by development teams to make the systems they design and operate more reliable. Build and maintain automation tools to streamline repetitive tasks and improve system reliability. Build and maintain the platform for CPU/storage, GPU, and network lifecycle management to drive efficiency, accountability and support dynamic optimization of our resources. Implement fault-tolerant and resilient

About the Team The Privacy Team at OpenAI is committed to building a secure and trustworthy platform. Our area of responsibility encompasses all OpenAI products and systems that process user data. We provide cross-functional partners with the tools needed to ensure that all products adhere to the highest standards of data privacy and legal compliance. Our approach to prioritizing responsible data use is integral to OpenAI's mission of safely introducing Artificial General Intelligence (AGI) that offers widespread benefits. About the Role We’re in search of a Software Engineer with experience building data pipelines and working closely with members of the Legal team. This role is perfect for someone who's passionate about the intersection of systems, privacy, and legal compliance. You will architect, design, and write backend systems responsible for handling some of the most sensitive data at OpenAI. This role is based in Dublin, Ireland. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, build, and maintain back-end systems and services that power privacy and data compliance functions within our API products and consumer applications. Work closely with legal advisors and other engineers to respond to court orders and other legal processes, all while upholding strict data privacy and legal standards. Identify opportunities for automation and build the tools that enable other teams to automate tasks involving customer data. Develop and implement data handling policies and procedures in compliance with legal and ethical standards, ensuring the integrity and confidentiality of user data. You might thrive in this role if you: Have experience building data pipelines, especially for legal processes and investigative workflows. Can translate legal requirements into technical solutions and explain technical solutions to a non-technical audience. Take responsibility for problems from be

We’re looking for a Software Engineer to architect and build backend systems that enforce data privacy and automate compliance at scale. You’ll work closely with product, infrastructure, security, and legal teams to embed privacy-by-design into our data and access layers. This is a hands-on, high-impact role for an experienced engineer who is passionate about protecting user data while enabling innovation. What You’ll Do Design, build, and operate backend services that enforce policy-driven data access, lifecycle controls, and privacy protections. Develop distributed authorization and identity-aware enforcement mechanisms integrated directly into data services and control planes. Implement auditability, policy hooks, and enforcement observability to ensure compliance is continuously verifiable. Partner with Security, Legal, and Compliance to convert privacy requirements into scalable technical designs and developer-friendly APIs. Harden data platforms and backend services through schema-level controls and data handling constraints by default. Collaborate with infrastructure teams to ensure consistent enforcement across systems while minimizing duplicated implementations. Contribute patterns, libraries, and education that elevate trustworthy data access patterns across the organization. You Might Thrive in This Role If You Have 5+ years of industry experience building and operating backend or infrastructure systems in production. Strong software engineering fundamentals , with fluency in at least one major programming language (e.g., Python, Go, Rust, C++, Java). Experience with distributed authorization, RBAC/ACL systems, encryption-based access, or policy engines. Familiarity with global privacy regulations and their architectural implications. Ability to influence and collaborate with teams across legal, compliance, product, and engineering. A bias toward practical, impactful solutions that balance privacy protections with product needs. Nice to Have Experience wi

About the Team Our London-based team builds the backend systems that help ChatGPT scale reliably. We work on infrastructure close to the product, partnering with engineering teams to improve the performance, resilience, and operability of critical user-facing systems. Our work combines backend software engineering with distributed systems and production reliability. We build shared capabilities, improve high-traffic workflows, and make it easier to introduce new product functionality without compromising performance or availability. About the Role This role is for software engineers who want to build and evolve backend systems operating at significant scale. You’ll write production code, design shared infrastructure, and solve technical challenges involving performance, distributed systems, and system reliability. You’ll also own how those systems behave in production: how changes are rolled out, how issues are detected and diagnosed, and how recurring operational problems can be addressed through better software and system design. This is a strong fit for backend engineers who enjoy complex systems problems and want a direct connection between the infrastructure they build and the experience of ChatGPT users. In this role, you will: Design, build, and maintain backend systems supporting high-traffic ChatGPT experiences. Develop shared services, APIs, and infrastructure that help product teams build and launch new capabilities safely. Improve the performance, scalability, and efficiency of production systems as usage and product complexity grow. Build and improve systems for asynchronous processing and other large-scale backend workloads. Lead architectural improvements and infrastructure migrations while maintaining correctness, compatibility, and safe rollout and rollback. Strengthen monitoring, alerting, and diagnostics to detect problems early and reduce customer impact. Participate in on-call, incident response, and root-cause analysis, and turn operational lea

About the Team The Applications Engineering team works across research, engineering, product, and design to bring OpenAI’s technology to consumers and businesses. You’ll join the team responsible for running the core infrastructure that supports products like ChatGPT and the API. The systems we support include our kubernetes clusters, infrastructure deployment, our networking stack, cloud abstractions, and more. 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 The cloud infrastructure team builds and maintains infrastructure abstractions allowing OpenAI to ship products quickly and scalably. In this role, you will: Design and build the development and production platforms that power our products, enabling reliability and security at scale Ensure our infrastructure can scale to the next order of magnitude Help create a diverse, equitable, and inclusive culture that makes all feel welcome while enabling radical candor and the challenging of group think Like all other teams, we are responsible for the reliability of the systems we build. This includes an on-call rotation to respond to critical incidents as needed. You might thrive in this role if you: Have 5+ years building core infrastructure Have experience operating orchestration systems such as Kubernetes at scale Have experience building abstractions over cloud platforms Take pride in building and operating scalable, reliable, secure systems Are comfortable with ambiguity and rapid change About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. About the Role On the Accelerators team, you will help OpenAI evaluate and bring up new compute platforms that can support large-scale AI training and inference. Your work will range from prototyping system software on new accelerators to enabling performance optimizations across our AI workloads. You’ll work across the stack, collaborating with both hardware and software aspects - working on kernels, sharding strategies, scaling across distributed systems, and performance modeling. You'll help adapt OpenAI's software stack to non-traditional hardware and drive efficiency improvements in core AI workloads. This is not a compiler-focused role, rather bridging ML algorithms with system performance - especially at scale. In this role, you will: Prototype and enable OpenAI's AI software stack on new, exploratory accelerator platforms. Optimize large-scale model performance (LLMs, recommender systems, distributed AI workloads) for diverse hardware environments. Develop kernels, sharding mechanisms, and system scaling strategies tailored to emerging accelerators. Collaborate on optimizations at the model code level (e.g. PyTorch) and below to enhance performance on non-traditional hardware. Perform system-level performance modeling, debug bottlenecks, and drive end-to-end optimization. Work with hardware teams and vendors to evaluate alternatives to existing platforms and adapt the software stack to their architectures. Contribute to runtime improvements, compute/communication over

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet High Performance Computing (HPC) team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automati

About the Team The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls. Our work spans data inventory and mapping, classification and lineage, retention and deletion, access governance, purpose and usage controls, auditability, and lifecycle automation. We aim to make policy-aligned data handling the default while giving teams clear, reliable primitives for building and operating products at scale. About the Role We are looking for an experienced Software Engineer to drive the architecture and execution of user data governance across OpenAI. You will define technical direction, build shared platforms and controls, and lead cross-functional programs that make data flows discoverable, policies enforceable, and ownership explicit. This role is well suited to a senior engineer who can move between deep systems design and organization-wide influence, turn ambiguous requirements into pragmatic roadmaps, and operate high-trust systems end to end. This position is based in San Francisco. Relocation assistance is available. In this role, you will: Set the technical strategy and architecture for user data governance across data mapping, classification, lineage, retention, deletion, access, and permitted usage. Design and build shared services, APIs, metadata systems, and policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable. Establish reliable inventories of user data, system ownership, data flows, and policy applicability across products, infrastructure, analytics, and research systems. Partner with Product, Data, Infrastructure, Security, and Legal leaders to define decision rights, translate requirements into controls, and drive adoption across teams. Own governance systems

About the team The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the role As a software engineer on the Fleet Hardware team, you will be responsible for the reliability and uptime of all of OpenAI’s compute fleet. Minimizing hardware failure is key to research training progress and stable services, as even a single hardware hiccup can cause significant disruptions. With increasingly large supercomputers, the stakes continue to rise. Being at the forefront of technology means that we are often the pioneers in troubleshooting these state-of-the-art systems at scale. This is a unique opportunity to work with cutting-edge technologies and devise innovative solutions to maintain the health and efficiency of our supercomputing infrastructure. Our team empowers strong engineers with a high degree of autonomy and ownership, as well as ability to effect change. This role will require a keen focus on system-level comprehensive investigations and the development of automated solutions. We want people who go deep on problems, investigate as thoroughly as possible, and build automation for detection and remediation at scale. In this role, you will: Build and maintain automation systems for provisioning and managing server fleets. Develop tools to monitor server health, performance, and lifecycle events. Collaborate with clusters, networking, and infrastructure teams. Partner with external operators to ensure a high level of quality. Identify and fix performance bottlenecks and inefficiencies. Continuously improve automation to reduce manual work