Software Engineer, Frontier Clusters Infrastructure

About the TeamThe Frontier Systems team at OpenAI builds, launches, and supports the largest supercomputers in the world that OpenAI uses for its most cutting edge model training.We take data center designs, turn them into real, working systems and build any software needed for running large-scale frontier model trainings.Our mission is to bring up, stabilize and keep these hyperscale supercomputers reliable and efficient during the training of the frontier models.About the RoleWe are looking for engineers to operate the next generation of compute clusters that power OpenAI’s frontier research.This role blends distributed systems engineering with hands-on infrastructure work on our largest datacenters. You will scale Kubernetes clusters to massive scale, automate bare-metal bring-up, and build the software layer that hides the complexity of a magnitude of nodes across multiple data centers.You will work at the intersection of hardware and software, where speed and reliability are critical. Expect to manage fast-moving operations, quickly diagnose and fix issues when things are on fire, and continuously raise the bar for automation and uptime.In this role, you will:Spin up and scale large Kubernetes clusters, including automation for provisioning, bootstrapping, and cluster lifecycle managementBuild software abstractions that unify multiple clusters and present a seamless interface to training workloadsOwn node bring-up from bare metal through firmware upgrades, ensuring fast, repeatable deployment at massive scaleImprove operational metrics such as reducing cluster restart times (e.g., from hours to minutes) and accelerating firmware or OS upgrade cyclesIntegrate networking and hardware health systems to deliver end-to-end reliability across servers, switches, and data center infrastructureDevelop monitoring and observability systems to detect issues early and keep clusters stable under extreme loadYou might thrive in this role if you:Have deep experience operating or scaling Kubernetes clusters or similar container orchestration systems in high-growth or hyperscale environmentsBring strong programming or scripting skills (Python, Go, or similar) and familiarity with Infrastructure-as-Code tools such as Terraform or CloudFormationAre comfortable with bare-metal Linux environments, GPU hardware, and large-scale networkingEnjoy solving fast-moving, high-impact operational problems and building automation to eliminate manual workCan balance careful engineering with the urgency of keeping mission-critical systems runningQualificationsExperience as an infrastructure, systems, or distributed systems engineer in large-scale or high-availability environmentsStrong knowledge of Kubernetes internals, cluster scaling patterns, and containerized workloadsProficiency in cloud infrastructure concepts (compute, networking, storage, security) and in automating cluster or data center operationsBonus: background with GPU workloads, firmware management, or high-performance computingAbout OpenAIOpenAI 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 to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic. For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.Background checks for applicants will be administered in accordance with applicable la ... (truncated, view full listing at source)