Cluster Head Last Mile in San Francisco

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 You will build the model runtime within the inference engine that executes complex, frontier models at scale on OpenAI’s custom silicon. The runtime will sit between models running on the hardware and the upper layers of the cluster serving software stack, translating demanding inference workloads into efficient execution while optimizing for throughput, latency, utilization, and reliability. You will work across model architecture, distributed systems, compilers, kernels, and silicon to design a production-grade runtime comparable in ambition to systems such as vLLM and SGLang, but customized and optimized for OpenAI’s AI accelerator. Your work will shape how new model capabilities map onto the platform and how quickly custom silicon can deliver meaningful performance in production. In this role, you will: Design and implement the LLM inference runtime for frontier models running on custom silicon. Build scheduling, continuous batching, memory management, KV-cache management, and execution orchestration for high-performance inference. Develop distributed execution strategies across chips, hosts, and racks, including model partitioning, communication, and synchronization. Optimize end-to-end latency, throughput, memory efficiency, and hardware utilization across diverse model architectures and serving workloads. Partner with kernel, compiler, architecture, and silicon teams to co-design interfaces and remove performance bottlenecks across the stack. Enable new

About the Team This team builds and operates the systems that enable OpenAI researchers to run reliable, scalable, and efficient research workflows. The team sits close to research and works across infrastructure, systems, and automation to make sure researchers have the tools and environments they need to move quickly. The work spans software engineering, infrastructure, systems administration, cluster operations, and reliability engineering. As OpenAI’s infrastructure evolves from bespoke bare-metal systems toward more standard, scalable platforms, the team needs engineers who can understand how systems work end-to-end and build the right abstractions without reinventing the wheel. About the Role As a Software Engineer on this team, you will build and operate the infrastructure that supports frontier research and critical research-facing systems. You will work on systems that sit close to the metal, but the role is not limited to classic operations or sysadmin work. We are looking for someone who can reason about networking, bootstrapping, Kubernetes, scalability, automation, and reliability - while also writing software to make these systems better over time. This role is a strong fit for an independent, high-ownership engineer who enjoys reliability-heavy infrastructure work but still wants to build. You do not need to come in as a kernel expert or highly algorithmic optimization engineer, but you should be deeply curious about infrastructure, comfortable debugging complex systems, and excited to support researchers doing novel work. We expect you to: Build and operate reliable infrastructure for research workloads and research-facing services. Support and improve systems across data infrastructure, processing, crawl and ingest, caching, search, observability, and clusterwide services. Improve cluster bootstrapping, provisioning, automation, and deployment workflows. Debug issues across networking, compute, storage, orchestration, and service reliability layers.

This role will support the fleet infrastructure team at OpenAI. The fleet team focuses on running the world’s largest, most reliable, and frictionless GPU fleet to support OpenAI’s general purpose model training and deployment. Work on this team ranges from Maximizing GPUs doing useful work by building user-friendly scheduling and quota systems Running a reliable and low maintenance platform by building push-button automation for kubernetes cluster provisioning and upgrades Supporting research workflows with service frameworks and deployment systems Ensuring fast model startup times though high performance snapshot delivery across blob storage down to hardware caching Much more! About the Role As an engineer within Fleet infrastructure, you will design, write, deploy, and operate infrastructure systems for model deployment and training on one of the world’s largest GPU fleet. The scale is immense, the timelines are tight, and the organization is moving fast; this is an opportunity to shape a critical system in support of OpenAI's mission to advance AI capabilities responsibly. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design, implement and operate components of our compute fleet including job scheduling, cluster management, snapshot delivery, and CI/CD systems. Interface with researchers and product teams to understand workload requirements Collaborate with hardware, infrastructure, and business teams to provide a high utilization and high reliability service You might thrive in this role if you: Have experience with hyperscale compute systems Possess strong programming skills Have experience working in public clouds (especially Azure) Have experience working in Kubernetes Execution focused mentality paired with a rigorous focus on user requirements As a bonus, have an understanding of AI/ML workloads About OpenAI OpenAI is an AI resea

About the Team The Core Network Engineering team owns the end-to-end networking stack that connects OpenAI’s compute infrastructure — spanning global WAN/edge connectivity, data-center networking, and high-performance host/xPU networking used for large-scale training and inference workloads. This team is responsible for ensuring networking is never the bottleneck to model training efficiency, cluster reliability, or fleet expansion. They design and operate the systems that provide predictable, high-throughput, low-latency connectivity across some of the world’s most advanced AI infrastructure. About the Role We’re looking for engineers to help build and operate the networking foundation behind OpenAI’s frontier AI systems. Depending on your background and area of focus, you may work across host networking, datacenter fabrics, or global WAN infrastructure. The problems span low-level systems software, distributed infrastructure, protocol readiness, observability, performance engineering, automation, and large-scale network operations. You’ll work on systems where microseconds of latency, tail performance, and network reliability directly impact model training efficiency and production serving performance. This role is ideal for engineers who enjoy operating close to the hardware/software boundary and solving performance-critical infrastructure problems at massive scale. In this role, you will: Design, build, and operate networking systems that support large-scale AI training and inference infrastructure Improve performance, reliability, and scalability across host networking, datacenter fabrics, and WAN systems Develop automation for provisioning, configuration management, validation, upgrades, and lifecycle management of networking infrastructure Build tooling and observability systems for network health, performance analysis, debugging, and automated remediation Optimize network performance across technologies such as RDMA, RoCE, InfiniBand, Ethernet, and high-perf

About the Team OpenAI’s Hardware organization develops system and infrastructure solutions tailored to the demands of advanced AI workloads. We work across the full stack—from silicon to system integration—partnering closely with internal teams and external vendors to define and deliver next-generation AI infrastructure. Our team focuses on defining scalable, high-performance system architectures and reference designs that balance performance, cost, and operational efficiency across rapidly evolving technologies. About the Role We are seeking a 3P Architect to define and drive rack- and cluster-level reference designs in collaboration with external partners. This role is responsible for translating workload requirements and system-level goals into concrete architectures, aligning partners on critical design attributes, and ensuring vendor roadmaps meet our infrastructure needs. You will work closely with performance modeling and internal architecture teams to evaluate tradeoffs, while owning the end-to-end definition and execution of third-party system designs. This includes identifying gaps in current technologies, driving vendor development, and shaping future infrastructure capabilities. This role requires strong system intuition, cross-functional leadership, and the ability to operate effectively across internal teams and external ecosystems. 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 Define rack- and cluster-level reference architectures for AI infrastructure deployments. Translate workload requirements into clear system design specifications and partner deliverables. Collaborate with performance modeling teams to evaluate architectural tradeoffs and system behaviors. Align internal stakeholders and external partners on critical system attributes (performance, cost, power, reliability, scalability). Identify gaps in current technology offerings and dr

About the Team: Compute Infrastructure builds the platform that turns enormous amounts of compute into a reliable engine for frontier AI. We design, provision, schedule, operate, and optimize the systems that connect accelerators, CPUs, networks, storage, data centers, orchestration software, agent infrastructure, developer tools, and observability into one coherent experience for researchers and product teams. Our work spans the entire stack: capacity planning and cluster lifecycle, bare-metal automation, distributed systems, Kubernetes and scheduling, deep system optimization, high-performance networking, storage, fleet health, reliability, workload profiling, benchmarking, and the developer experience that lets teams use enormous compute systems with confidence. At this scale, small improvements to communication, scheduling, hardware efficiency, or debugging workflows can compound into meaningful research velocity. We are hiring across Compute Infrastructure rather than for a single narrow team, and we use this opening to match strong engineers to the problems where they can have the most leverage. About the Role We are looking for engineers who want to build the compute platform behind OpenAI's research and products. You may not be the strongest in low-level systems, high-performance computing, distributed infrastructure, reliability, CaaS, agent infrastructure, developer platforms, tooling, or the user experience around infrastructure. What matters is that you can reason carefully about complex systems, write durable software, and raise the quality and velocity of the people around you. Depending on your background and interests, you might work close to hardware, close to users, on CaaS and agent infrastructure, or on the control planes and data planes in between. You could help bring new supercomputing capacity online, optimize training workloads from profiler traces and benchmarks, improve NCCL and collective communication behavior, reason about GPUs, NICs, t

About the Team OpenAI’s Infrastructure organization builds the systems that power frontier AI workloads at global scale. As compute demand accelerates, our ability to rapidly convert infrastructure investments into usable production capacity has become mission critical. The CPU / Storage / PoP / WAN team is responsible for the end-to-end infrastructure layers required to bring compute online: server and cluster activation, storage platforms, Points of Presence (PoPs), backbone connectivity, and global network expansion. We operate across first-party facilities, colocation environments, and strategic cloud partners to ensure OpenAI can scale reliably and quickly. About the Role We are seeking a highly technical Program Manager to lead execution across CPU, Storage, PoP, and WAN infrastructure programs that directly unlock OpenAI’s next generation compute capacity. In this role, you will own complex cross-functional programs spanning compute cluster activation, storage deployment, PoP bring-up, and backbone expansion. You will coordinate hardware readiness, site readiness, network pathing, storage availability, vendor execution, and engineering dependencies required to turn contracted infrastructure into live training and inference capacity. This role requires strong technical fluency across hardware systems, network infrastructure, storage architecture, and deployment execution. You should be comfortable operating from rack-level implementation details through executive-level capacity planning discussions. This role is based in San Francisco, CA, with travel as needed. Key Responsibilities Lead end-to-end execution of CPU / GPU cluster activation programs across OpenAI’s global infrastructure footprint Drive readiness to convert contracted compute capacity into schedulable production clusters Own deployment programs for new PoPs, backbone nodes, WAN expansion, and interconnection initiatives Build integrated schedules spanning procurement, logistics, installation, st

About the Team OpenAI's Industrial Compute organization builds and operates the infrastructure required to train and serve frontier AI models. The Capacity Planning team connects rapidly changing research and product demand with the compute, networking, storage, power, data center, hardware, and operational resources required to make that demand executable. About the Role We are seeking a Technical Program Manager to build and lead capacity planning across OpenAI's large-scale AI infrastructure. You will translate uncertain workload demand into clear infrastructure requirements, allocation decisions, supply commitments, activation priorities, and long-range capacity strategies. This role sits at the intersection of research, engineering, infrastructure, finance, sourcing, deployment, and operations. You will create the planning models, operating cadences, governance mechanisms, and source-of-truth systems that allow teams to understand what capacity is required, what is available, what is at risk, and what decisions must be made. This is not a finance-only forecasting or reporting role. Success requires technical fluency across the infrastructure stack, strong analytical judgment, and the ability to move consequential decisions forward when requirements, timelines, and supply conditions change quickly. Key Responsibilities Own capacity-planning processes across near-term workload allocation, quarterly execution, and longer-range infrastructure horizons. Translate research, training, inference, and product demand into compute, accelerator, cluster, networking, storage, rack, power, and site requirements. Develop scenarios that make assumptions, confidence levels, constraints, sensitivities, and decision points explicit. Reconcile requested demand against contracted, delivered, installed, activated, and workload-usable capacity. Partner with research and engineering teams to understand workload priorities, technical dependencies, utilization patterns, and changing req

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're looking for a hands-on Operations Manager to own the operational and analytical supply side of our GPU fleet. Key focus areas: GPU fleet lifecycle, health, observability, utilization monitoring, and remediation across our neocloud and bare metal environments. We contract for a fixed amount of compute capacity. GPUs drift from healthy to unhealthy over time, and this role minimizes that downtime to keep the maximum number of GPUs healthy at any given moment. This is an operator role, not people management. You'll drive execution through clear processes, metrics, reporting, vendor coordination, and cross-functional alignment.. RESPONSIBILITIES Core Responsibilities: Drive suppliers to keep the maximum amount of the GPU fleet online and healthy. Maintain a live reconciliation of contracted vs. provisioned vs. healthy vs. utilized capacity, broken out by supplier and by cluster maximizing the number of healthy GPUs. Supplier-attributed fleet health accountability: own replacement SLAs, mean time to repair (MTTR), and RMA cycle times for every in-scope supplier. SLA monitoring, credit claims, and remedy enforcement: track SLA performance against contract terms, file and pursue credit claims, and drive remediation plans when suppliers fall short. Drive internal communications where suppliers need to perform maintenance to ensure all Baseten stakeholders are aware of activities that impact availability. Scope and

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products. THE ROLE We're hiring a Product Data Scientist to establish how product decisions at Baseten are made with data. You'll work directly with Product and Engineering, alongside GTM to determine measurement, strategy, experimentation and implementation. This is a foundational, hands-on role. You'll define what success looks like across a technical, usage-based platform and turn ambiguous questions into analyses, forecasts, and experiments that shape product strategy. You'll work from clickstream and product events through inference telemetry and observability data, helping Baseten make faster decisions about reliability, performance, adoption and developer experience. RESPONSIBILITIES Partner directly with Product and Engineering: frame the questions that matter, define success criteria, and turn analysis into roadmap, launch, and prioritization decisions. Define how product success is measured: establish metrics across activation, adoption, retention, expansion, reliability and user experience. Support experimentation and launches: design measurement plans, analyze A/B experiments and controlled rollouts, and translate results into product decisions. Diagnose reliability and scaling behavior: join customer signals with request, replica, deployment, and cluster telemetry to find patterns in release bottlenecks, unhealthy replicas, and models without traffic. Define the enterprise customer journey and measure feature adoption

About the Team The Core Services organization builds and runs the mission-critical online services that product teams rely on in production. We own foundational distributed systems and platform capabilities that enable reliable execution, high-performance services, and large-scale file/data needs across our products. This team is distinct from developer infrastructure and data infrastructure—our focus is production service foundations and core runtime services. About the Role We’re hiring an Engineering Manager, Core Services to help lead teams responsible for highly reliable, high-scale distributed systems that sit on the critical path for OpenAI products. Your team will own foundational production systems that OpenAI’s product engineering teams build on. You’ll collaborate closely with product and infrastructure partners to ship reliable services quickly, and help scale systems and teams as OpenAI grows. You’ll partner closely with senior engineering leaders to scale the org, mature operations, and drive major platform initiatives. This role requires strong technical ability. You’ll be responsible for: Managing and growing a high-performing team of infrastructure engineers. Leading teams building and operating large, critical production platforms, including cluster reliability, scaling, and rollout safety. Building and operating mission-critical distributed systems with strong operational rigor (SLOs, incident response, capacity planning, reliability). Setting technical direction for platform foundations such as workflow/orchestration capabilities, large-scale file/blob/storage services, and core service foundations. Partnering with a broad set of stakeholders, including product engineering, adjacent infrastructure teams, and (where relevant) finance/cost partners. Coaching, mentoring, and developing engineers and emerging leaders. You might thrive in this role if you: Have significant experience leading teams that run mission-critical infrastructure in production

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE As an OS / K8s Systems Engineer at Baseten, you’ll build the automation and systems that turn raw GPU hardware into production-ready compute. From provisioning to orchestration, you’ll own the software layer that makes our infrastructure reproducible, scalable, and reliable across data centers. This is a senior, hands-on role focused on building systems not operating them. You’ll work close to the metal designing OS images, building provisioning pipelines, and automating cluster bring-up from scratch. Your work will define how quickly we can turn new capacity into usable compute. EXAMPLE INITIATIVES Zero-to-cluster automation Build workflows that take new hardware from unprovisioned to fully operational cluster. Provisioning systems Design PXE-based or equivalent systems for imaging and lifecycle management. Reproducible infrastructure — Ensure clusters deploy consistently across data centers. RESPONSIBILITIES Own the end-to-end automation of cluster bring-up and lifecycle management. Build and maintain OS images, provisioning systems, and configuration pipelines. Deploy and operate cluster orchestration platforms (Kubernetes, Slurm, or similar). Design systems for reproducibility across sites and hardware generations. Automate upgrades, rollouts, and failure recovery. Optimize system performance, including GPU utilization and networking. Partner with hardware and network teams to validate and improve system b

ABOUT BASETEN Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F , led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to to ship AI products. THE ROLE At Baseten, we’re looking for a Technical Program Manager to drive our most complex, cross-cutting infrastructure programs. This role will operate across all domains of AI infrastructure, from the GPUs up to the multi-cluster orchestration layer. This is an execution-first role. The work is less about owning a single system and more about imposing order on ambiguity: standing up the right structures, driving decisions to closure, and making sure nothing falls through the cracks across dozens of stakeholders. If you take satisfaction in turning a chaotic, half-defined initiative into a predictable, well-governed program, this role is for you. RESPONSIBILITIES Own complex migrations end to end. Lead large-scale infrastructure migrations across teams and domains. This will involve scoping the work, sequencing dependencies, managing risk, and driving them to completion without surprises. Drive process across infrastructure. Establish and run the operating rhythms that keep programs healthy: planning cadences, status reporting, decision logs, risk reviews, and escalation paths. Make the process light enough that teams adopt it and rigorous enough that it actually works. Help managers build the right structures. Partner with engineering managers and leads to design the team structures, ownership boundaries, and working models a program needs to succeed. Spot gaps in accountability before they become problems. Own fo

About the Team The compute infrastructure team runs the GPU fleet and large-scale compute clusters that serve the models backing ChatGPT and the API, while also supporting training workloads for our next generation models. We operate a large, modern GPU fleet and provide a unified platform for other OpenAI teams to seamlessly run production Applied AI and Research training workloads. 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 You will be part of an engineer-first TPM team as a Technical Program Manager for Compute Infrastructure who owns the end-to-end delivery of large-scale GPU clusters, partnering with engineers to bring clusters online across external providers and partners. You’ll run a broad, parallel portfolio spanning hardware, networking, power, and cooling—driving execution, risk management, and crisp alignment from working teams through leadership to deliver production-ready capacity at scale. 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: Lead end-to-end delivery of both New Compute SKUs and large-scale GPU clusters across an external partner ecosystem while supporting capacity planning for training and inference. Ability to contextually drive multi-threaded bring-up programs spanning hardware, networking, power, and cooling—owning plans, dependencies, and critical paths. Interface with chip providers to derisk long-term onboarding to new hardware platforms by working across kernels, comms, hardware, and scheduling engineering teams. Build and operationalize program mechanisms (roadmaps, milestones, risk registers, runbooks) that make delivery predictable at massive scale. Partner with engineering to improve cluster turn-up reliability, repeatability, and automation

The Fleet team at OpenAI supports the computing environment that powers our cutting-edge research and product development. We oversee large-scale systems that span data centers, GPUs, networking, and more, ensuring high availability, performance, and efficiency. Our work enables OpenAI’s models to operate seamlessly at scale, supporting both internal research and external products like ChatGPT. We prioritize safety, reliability, and responsible AI deployment over unchecked growth. About the Role The Software Engineer, Operating Systems & Orchestration will focus on building systems to manage hardware, configurations, vendors, and the people interacting with our infrastructure. You will design and develop solutions that integrate individual nodes and servers into unified clusters, directly contributing to advancing AI research by streamlining the overall research user experience. This role is based in San Francisco, CA. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. In this role, you will: Design and build systems to manage both cloud and bare-metal fleets at scale. Develop tools that integrate low-level hardware metrics with high-level job scheduling and cluster management algorithms. Leverage LLMs to coordinate vendor operations and optimize infrastructure workflows. Automate infrastructure processes, reducing repetitive toil and improving system reliability. Collaborate with hardware, infrastructure, and research teams to ensure seamless integration across the stack. Continuously improve tools, automation, processes, and documentation to enhance operational efficiency. You might thrive in this role if you: Have strong software engineering skills with experience in large-scale infrastructure environments. Possess broad knowledge of cluster-level systems (e.g., Kubernetes, CI/CD pipelines, Terraform, cloud providers). Have deep expertise in server-level systems (e.g., systems, containerization, Chef,