Reliability Engineer Iii in United States

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 Senior Actuator Design and Integration Engineer to lead the development of custom electromechanical actuators for advanced robotic systems. You will own actuator development from early architecture and concept generation through prototype validation and system integration, partnering closely with mechanical, electrical, controls, firmware, reliability, and manufacturing teams. This role focuses on the design, integration, and validation of precision electromechanical systems, including motors, transmissions, sensing, structural components, and thermal architectures. You will help drive actuator development across the full engineering lifecycle while establishing scalable design, test, and integration practices for future robotic platforms. This role is based in San Francisco, CA, and requires in-person presence 4 days a week. In this role, you will Lead the architecture, design, and integration of custom robotic actuators, including motors, transmissions, sensing, thermal systems, structural components, and packaging. Define actuator requirements and system-level trade studies around torque density, bandwidth, efficiency, thermal performance, backdrivability, inertia, reliability, manufacturability, and cost. Design precision electromechanical assemblies with strong attention to tolerances, alignment, load paths, thermal expansion, sealing, wear, and serviceability. Drive actuator integration into robotic systems, partnering closely with controls, firmware, electrical, and robotics software teams to optimize closed-loop pe

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

About the Team OpenAI, in close collaboration with our capital partners, is building the world’s most advanced AI infrastructure ecosystem. Our Industrial Compute organization develops and deploys large-scale AI campuses designed to support the next generation of frontier model training and inference workloads. The Hardware Operations team is responsible for ensuring the reliability, availability, and lifecycle health of OpenAI’s compute infrastructure. We partner closely with Data Center Operations, Fleet Health Engineering, Manufacturing, Network Infrastructure, Capacity Planning, and our infrastructure partners to maintain world-class operational performance across rapidly expanding AI environments. As we scale globally, we are building the operational frameworks, reliability standards, and sustaining engineering practices required to support thousands of GPUs and servers across multiple campuses. About the Role We are seeking a Datacenter Hardware Technician Lead to serve as the senior on-site technical authority for hardware reliability and fleet health at one of OpenAI’s flagship AI campuses. This role operates at the intersection of hardware operations, sustaining engineering, and fleet reliability. You will partner closely with Cloud Service Provider operations teams, OpenAI fleet-health engineers, hardware engineering teams, and OEM vendors to identify, diagnose, and resolve hardware issues affecting production systems. Beyond day-to-day operational support, you will drive root cause investigations, reliability improvement initiatives, lifecycle management programs, and operational readiness efforts. You will help establish hardware maintenance standards, operational procedures, and best practices that scale across future OpenAI infrastructure deployments. The ideal candidate combines deep hands-on datacenter hardware expertise with strong troubleshooting, failure analysis, and cross-functional leadership skills. Candidates must be able to sit onsite at our

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 operational in how we execute, and we support every product and research effort at OpenAI. Our tenets include prioritizing for impact, enabling researchers and developers, preparing for future transformative technologies, and fostering a strong, collaborative security culture. About the Role OpenAI is seeking a Security Software Engineer to join the Infrastructure Security (InfraSec) team. InfraSec safeguards the core of OpenAI’s research and production environments—GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter spans everything from bare-metal hardware and firmware to Kubernetes clusters, service meshes, and the data pathways that carry highly sensitive model weights and user data. As a Security Software Engineer, you will design and build critical foundational services, such as authentication systems, egress/ingress proxies, access brokers, and key management platforms, that demand high standards of reliability, scalability, and software craftsmanship. These systems form the security backbone of OpenAI’s supercomputing environment and must remain robust under intense scale and adversarial pressure. In this role, you will: Architect and implement production-grade security services (e.g., auth services, access brokers, secure proxies, key-management infrastructure) that provide strong guarantees across hardware, operating systems, Kubernetes, networks, and CI/CD. Partner with infrastructure and research engineers to embed security into high-performance compute clusters, enabling rapid model training and deployment without compromising protection. Develop automation and detection tooling to continuously identif

About the Team At OpenAI, we’re building safe and beneficial artificial general intelligence. We deploy our models through ChatGPT, our APIs, and other cutting-edge products. Behind the scenes, making these systems fast, reliable, and cost-efficient requires world-class infrastructure. The Caching Infrastructure team is responsible for building a caching layer that powers many critical use cases at OpenAI. We aim to provide a high-availability, multi-tenant cache platform that scales automatically with workload, minimizes tail latency, and supports a diverse range of use cases. We’re looking for an experienced engineer to help design and scale this critical infrastructure. The ideal candidate has deep experience in distributed caching systems (e.g., Redis, Memcached), networking fundamentals, and Kubernetes-based service orchestration. In This Role, You Will: Design, build, and operate OpenAI’s multi-tenant caching platform used across inference, identity, quota, and product experiences. Define the long-term vision and roadmap for caching as a core infra capability, balancing performance, durability, and cost. Collaborate with other infra teams (e.g., networking, observability, databases) and product teams to ensure our caching platform meets their needs. You Might Thrive In This Role If You: Have 5+ years of experience building and scaling distributed systems, with a strong focus on caching, load balancing, or storage systems. Have deep expertise with Redis, Memcached, or similar solutions, including clustering, durability configurations, client-side connection patterns, and performance tuning. Have production experience with Kubernetes, service meshes (e.g., Envoy), and autoscaling systems. Think rigorously about latency, reliability, throughput, and cost in designing platform capabilities. Thrive in a fast-paced environment and enjoy balancing pragmatic engineering with long-term technical excellence. About OpenAI OpenAI is an AI research and deployment company d

About the team The OpenAI for Government team is a dynamic, mission-driven group leveraging frontier AI to transform how governments achieve their missions. Our team works to empower public servants with secure, compliant AI tools (e.g., ChatGPT Enterprise, ChatGPT Gov) and mission-aligned deployments that meet government technical requirements with strong reliability and safety. About the role Forward Deployed Engineers (FDEs) lead complex deployments of frontier models in production. You will embed with our most strategic government and public sector customers—where model performance matters, delivery is urgent, and ambiguity is the default. You’ll map their problems, structure delivery, and ship fast. This includes scoping, sequencing, and building full-stack solutions that create measurable value, while driving clarity across internal and external teams. You will work directly with defense, intelligence, and federal stakeholders as their technical thought partner, guiding adoption, maximizing mission impact, and ensuring successful deployments at scale. Along the way, you’ll identify reusable patterns, codify best practices, and share field signal that influences OpenAI’s roadmap. This role is based in Washington DC, Seattle or San Francisco. We use a hybrid work model of 3 days in the office per week. We offer relocation assistance. Travel up to 50% is required, including on-site work with customers. In this role you will Own technical delivery across multiple government deployments, from first prototype to stable production. Deeply embed with public sector customers to design and build novel applications powered by OpenAI models. Enable successful deployments across customer environments by delivering observable systems spanning infrastructure through applications. Prototype and build full-stack systems using Python, JavaScript, or comparable stacks that deliver real mission impact. Proactively guide customers on maximizing business and operational value from

About the Team The Applied 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. This role is based in San Francisco, CA. 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 This role is exclusively based in our San Francisco HQ. We offer relocation assistance to new employees. 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 depl

About the Team The Support Automation team at OpenAI scales the organization by applying cutting-edge AI models to real-world challenges, automating and enhancing work across the organization. From customer operations to engineering, we develop an ecosystem of automation products that empower our colleagues and drive impact. We're passionate about crafting products that serve those around us, blending rapid prototyping with a focus on long-term quality and reliability. By creating reusable solutions, we create patterns that can be applied across diverse domains within OpenAI. TLDR: this team leverages OpenAI technology to improve OpenAI, and you’ll have the opportunity to leverage the full extent of our tech (both public and pre-released) to accomplish this mission. About the Role We’re looking for a Backend Software Engineer with experience working in ML/LLM-heavy domains to help to design and build an evals infrastructure that measures the quality of OpenAI’s support automation. This is a deeply technical and highly cross-functional role where you’ll build robust systems and backend services that serve as the foundation for how knowledge is created, accessed, and applied across OpenAI. The role will especially focus on working closely with Data Science and Research partners to design and build evals at scale. In this role, you will: Design eval pipelines that are reliable, reproducible, and extendable Build the infrastructure for continuous eval monitoring frameworks (regression/drift monitoring, building robust golden datasets) along with feedback loops that ultimately strengthen support automation Design, build, and maintain backend services and APIs to support intelligent automation and knowledge systems Integrate and structure data across internal platforms, transforming it into formats optimized for use by downstream systems and AI workflows. Collaborate closely with data, research, and engineering teams to integrate OpenAI models into high-leverage workflows

About the Team We are building general-purpose robotics. In the short term, we are focused on robots to support skilled workers to build our future infrastructure. In the long term, we imagine everyone having a personal robot doing anything they need. Progress is rapid, and based on a foundation of co-design between robotics hardware and ML research. About the Role As a Firmware Engineer, you will define and drive the architecture of embedded systems for next-generation hardware products. You will own foundational firmware decisions across real-time execution, device bring-up, hardware interfaces, fault handling, safety mechanisms, and production readiness. We’re looking for someone with deep experience building safety-critical or high-consequence systems, where failures can have meaningful consequences. You should be comfortable reasoning about risk, designing for diagnosability and graceful degradation, and creating engineering practices that raise the reliability bar for the entire team. You should also be unusually good at moving fast. Sometimes the right answer is a carefully reviewed architecture that will endure for years; sometimes it is getting a rough-but-useful prototype working by the end of the afternoon so the team can learn something concrete tomorrow. We value engineers who know the difference, make that call well, and can operate credibly in both modes. You will be both a technical leader and a hands-on builder: setting direction, reviewing critical designs, unblocking the hardest problems, and writing production firmware when it matters most. Our embedded stack uses a lot of Rust. Extensive experience in the language is a big help! 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: Rapidly bring up new hardware and set execution pace for the team. Lead firmware architecture for embedded systems spanning boot, RTOS/runtime behav

About the Team The Codex Research 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 the Codex Research team, you will improve the capabilities, reliability, and product fit of OpenAI's agentic models. You might own a research direction, build the infrastructure that makes large training runs faster and more trustworthy, create evals that reveal where models fail, or drive a capability from an idea through experimentation, integration, and launch. This role is intentionally broad. The strongest candidates are not defined by one method or subfield; they are people who can take an ambiguous capability problem and make progress across research, engineering, data, evals, and product. You should be excited to work on models that act in the world: writing and debugging code, using tools, calling functions, operating computers, collaborating with other agents, and completing valuable work on behalf of users. You will work with researchers, engineers, product teams, infrastructure teams, and safety/alignment partners to decide what should go into major model runs, measu

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’re looking for a GPU Inference Engineer to contribute to improvements in model serving efficiency for our Robotics research. This is a high-impact role where you’ll drive initiatives to optimize inference performance and scalability. You’ll also be engaged in model design, to help assist our researchers in developing inference-friendly models. This role is critical to scaling the team’s broader goals - it will directly enable leadership to focus on higher-leverage initiatives by building a stronger technical foundation. In this role you will: Perform engineering efforts focused on improving model serving, inference performance, and system efficiency Drive optimizations from a kernel and data movement perspective to improve system throughput and reliability Partner closely with research and product teams to ensure our models perform effectively at scale Design, build, and improve critical serving infrastructure to support Robotics growth and reliability needs You might thrive in this role if you: Have deep expertise in model performance optimization, particularly at the inference layer Have a strong background in kernel-level systems, data movement, and low-level performance tuning Are excited about scaling high-performing AI systems that serve real-world, multimodal workloads Can navigate ambiguity, set technical direction, and drive complex initiatives to completion 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. About OpenAI OpenAI i

About the Team The Applied team at OpenAI safely brings cutting-edge technology to the world. We have released widely used products such as ChatGPT, Sora, and the OpenAI API, powering models including GPT-5 and a growing set of multimodal capabilities across text, image, audio, and video. Our team also manages large-scale inference and platform infrastructure that supports these experiences at global scale. With much more on the horizon, our impact continues to grow. Our customers build fast-growing businesses using our APIs, unlocking product capabilities that were previously unimaginable. ChatGPT and Sora exemplify the breadth of what’s now possible across text, image, audio, and video experiences. As these capabilities expand, we prioritize the responsible use of our technology, emphasizing safe and thoughtful deployment over unchecked growth. Within Applied Engineering, the Ads Monetization team in Financial Engineering builds the core systems dealing with all the money flows for ChatGPT Ads. These systems are a combination of low-latency, high scale, high reliability, while being built in a financially correct, accurate, auditable and explainable way. This role sits at the intersection of ads delivery, data engineering, and financial systems. In this role, you will: Architect and build the core monetization systems for ChatGPT Ads. Build and operate the core services and pipelines that power ads monetization end-to-end, from event capture and validation through aggregation, pricing, metering, and ultimately producing billable outputs. Define and implement the source of truth for ads monetization data, including schemas, data models, and invariants that ensure outputs are consistent, explainable, and auditable. Own correctness and reconciliation: align production outputs with downstream invoicing/finance requirements, build controls/monitors, and close gaps through investigations and backfills. Develop across the stack to create comprehensive billing integration

About the Team OpenAI’s Applications Engineering organization builds and operates the products that bring our cutting-edge research to millions of users and developers worldwide. The Applied Foundations team owns the core product and platform layers that make those experiences possible — from identity & access, to safety to payments & commerce across all of our apps. Our teams span product engineering, infrastructure, and safety, working together to deliver technology that is reliable, secure, and trusted at global scale. About the Role You will be a Senior Android engineer on OpenAI’s Applied Foundations team, building the core mobile experiences that power how users sign up, manage their account, family features, pay for services, stay safe, and interact with OpenAI’s products with confidence. This role is about creating high-quality products as well as reusable Android foundations that product teams across different OpenAI apps depend on to ship quickly while meeting the highest standards for security, reliability, and user trust. You’ll own complex client-side systems spanning UI, networking, local state, payment integrations and Apple platform integrations, and work closely with backend, product, and safety partners to shape the architecture that supports OpenAI’s mobile ecosystem at global scale. You might thrive in this role if you: Have 4+ years of professional software engineering experience. Have a proven track record of building high-quality Android applications in production. Are fluent in Kotlin (and/or Java) and familiar with Android development tools and architecture components. Prioritize performance, security, and user experience in mobile development. Enjoy working cross-functionally to bring ambitious product ideas to life. Care deeply about performance, security, and user experience. About OpenAI OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We

About the Team The Monetization team is a new cross-functional group working across engineering, product, research, and design to build the foundational systems that will help OpenAI scale access to intelligence responsibly. Our mission is to develop user-first, privacy-preserving monetization products—including next-generation ads experiences—that strengthen user trust, unlock economic opportunity, and support OpenAI’s long-term innovation. Monetization plays a critical role in enabling OpenAI to continue pushing the boundaries of AI capabilities while ensuring the benefits of AGI are broadly shared. We believe monetization must be aligned with user value, uphold rigorous privacy and safety standards, and sustain a healthy ecosystem of developers and businesses. This team operates in a greenfield environment and moves quickly through prototyping, experimentation, and iterative deployment. We partner closely with Product, Design, and Research to bring research breakthroughs into real-world systems at global scale. About the Role We’re looking for an experienced Software Engineer to help build the core infrastructure behind OpenAI’s monetization and ads systems. In this foundational role, you’ll architect and implement distributed systems that power OpenAI’s monetization stack—focusing on reliability, performance, privacy, and large-scale operation. You’ll work across backend, systems, and platform layers to define and implement 0→1 infrastructure, partnering closely with Product, Design, and Research to shape the future of monetized AI experiences. Your work will enable both internal and external teams to build on safe, scalable, and robust monetization primitives. This role is exclusively based across our San Francisco & Seattles sites. We offer relocation assistance to new employees. In this role, you will: Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems Architect large-scale distributed systems that