Workload Porting And Performance Engineer in San Francisco

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry provides developer-first observability to over 4 million developers worldwide. The Events Analytics Platform (EAP) team is at the heart of that mission: it powers how all of Sentry's event data, such as errors, transactions, spans, profiles, replays, and metrics, is stored, queried, and analyzed. It also powers Sentry's latest AI push, Seer. The EAP team makes it possible for developers to efficiently search and debug across massive volumes of data, providing the context needed to understand and fix issues quickly. This team is also a cornerstone of Sentry's long-term strategy to become a context assembly and telemetry platform that unifies different signals so developers can see the complete picture. As an engineering manager on the EAP team, you will lead a group of engineers building and scaling one of Sentry's most critical data platforms. You will be responsible for driving architectural evolution, ensuring system stability, and mentoring a talented team. This is a highly visible leadership role with direct ties to Sentry's long-term product and platform strategy. What you'll do Grow and develop a team of engineers with high expectations for ownership and impact Set the technical and strategic direction for the team, balancing short-term stability with long-term architectural evolution Drive development of core EAP features, including support for complex analytical queries, dynamic routing logic across fidelity levels, storage and compute separation, and modern patterns for analytical storage Ensure EAP can support the workload demands of AI agents and MCP servers that unlock new AI capabilities fo

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 As a Global Capacity Manager focused on TPUs at Baseten, you will lead the "engine room" for our non-NVIDIA accelerator fleet, architecting, securing, and optimizing the Google Cloud TPU (and broader emerging accelerator) capacity that powers our customers' AI workloads. You'll own the end-to-end journey of capacity management for this fleet, from securing large-scale TPU pod allocations to building the automation that ensures reliable uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering, with a specific focus on the TPU ecosystem. You will act as the fleet orchestrator for Google's TPU architecture, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics as we diversify beyond NVIDIA. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the latest generation of TPU hardware, like Google's Trillium (v6e) architecture, and partnering closely with the Model Performance (MP) team to ensure workloads are tuned for TPU-specific execution. EXAMPLE INITIATIVES The TPU Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's TPU clusters, including pod slicing and topology planning Global Workload Orchestration: Bui

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 As a Global Capacity Lead at Baseten, you will lead the "engine room" of the company, architecting, securing, and optimizing the global GPU fleet that powers our customers' AI workloads. You’ll own the end-to-end journey of capacity management, from securing multi-million dollar GPU clusters to building the automation that ensures 99.9% uptime across multi-cloud environments. This role is a great fit for entrepreneurial engineers who want to bridge the gap between high-finance asset management and deep infrastructure engineering. You will act as the fleet orchestrator for the world's most advanced chips, ensuring Baseten never experiences a capacity outage while maintaining elite unit economics. To be clear, this is a high-stakes engineering role. You will be hands-on with Kubernetes orchestration while also leading specialized pods focused on the next generation of hardware, like NVIDIA’s Blackwell (B200) architecture. EXAMPLE INITIATIVES The B200 Frontier: Architecting the infrastructure readiness and deployment strategy for Baseten's first Blackwell GPU clusters. Global Workload Orchestration: Building "Multi-cloud Capacity Management" systems to move customer workloads seamlessly across regions to optimize cost and latency. Precision GPU Triage: Developing automated Go-based operators to identify, cordon, and repair unhealthy H100 nodes in under an hour. The Supply Chain of Intelligence: Partnering with lead

About the Team OpenAI's data and storage infrastructure spans data platforms, online databases, and file/object storage. These systems underpin data ingestion and processing, durable persistence, indexing and retrieval, and product file experiences. As frontier models and agents evolve how they use memory, history and snapshots, the underlying architecture increasingly shapes the capabilities products can deliver—and their latency, reliability, cost and efficiency. About the Role We are looking for a technically deep TPM to independently define and lead multiple programs across data platforms, online databases and storage infrastructure. You will connect model, product and data-consumer requirements to architecture, and work with the relevant engineering teams to take new capabilities through production adoption and repeatable expansion. The design scope is exabyte-scale storage and infrastructure spanning multiple millions of CPU cores. The challenge is not simply forecasting more resources: it is making complete, workload-ready capacity repeatable, with a clear path from product requirements through architecture, deployment and validation. A data pipeline, database query, file operation or execution snapshot can affect whether a product or agent succeeds; you will connect those outcomes to the systems underneath. 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: Translate model, product and data-platform needs into precise access patterns, consistency, durability, freshness, availability and scalability requirements. Connect memory, history, retrieval and resumable work to capability and end-to-end latency. Partner with engineering to transform data and storage architecture into repeatable scale units: standardized provisioning, placement, routing, data movement and readiness checks that bring storage, compute and networking online together.

About the Team The Industrial Security team enables OpenAI’s classified and national security work by building secure, compliant programs that support government customers and protect sensitive information. Within Industrial Security, the Personnel Security function ensures employees have the clearances, accesses, briefings, and government approvals required to support classified programs. We work closely with employees, program teams, government customers, and partners across Security, People, Recruiting, Legal, IT, and Facilities to make complex security processes accurate, timely, and understandable. About the Role As a Personnel Security Specialist, you will own the day-to-day personnel security operations that allow OpenAI employees to support classified government work. You will manage clearance and access requests, maintain government-system records, coordinate visits and briefings, support onboarding and offboarding, and guide employees through sensitive security requirements with discretion and care. We’re looking for a hands-on security professional who can independently manage a high-volume operational queue, keep cases and records organized, recognize when issues require escalation, and improve the processes behind the work. This role offers the opportunity to help build a modern personnel security function that supports important national security programs while delivering a thoughtful, responsive employee experience. This role is based in San Francisco, CA, or Washington, DC. We use a hybrid work model of three days in the office per week and offer relocation assistance to new employees. Additional onsite presence and occasional travel may be required based on classified program and government customer needs. In this role, you will: Own the daily personnel security workload from intake through completion, including clearance verification, access nominations, visit requests, onboarding, offboarding, briefings, and reporting actions. Process and track pe

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 The largest, most demanding enterprises run on Baseten, and they bring exacting requirements for how people, services, and agents access the platform. This is the founding role for our identity and authorization team within enterprise engineering. You'll own the identity and access layer of the Baseten platform: the authorization model, credential systems, and admin experiences that enterprise IT teams use to govern access for organizations like Harvey, HubSpot, and Notion. You'll design and build Baseten's fine-grained authorization system from the ground up to support the workflows customers depend on today while giving them cleaner, more precise ways to manage access as the platform grows. Authorization at Baseten requires low-latency permission checks at high request volume, consistent contracts and behaviors across the product suite, and strong security guarantees for mission-critical, highly regulated workloads. EXAMPLE INITIATIVES Recent and upcoming work in this area: Fine-grained authorization for users, service accounts, and agentic workloads: per-resource permissions at the organization, team, and workload scope to support both common workflows and complex enterprise access policies Programmatic authentication allowing high-compliance customers to connect service principles securely via short-lived, workload-based credentials Agent credentials that grant an agent exactly the access it needs for the gi

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 work on the systems software strategy and execution that brings new AI silicon from first power-on to a fully integrated system running production-representative models at expected functionality and performance. You will define how software exercises and validates compute, memory, interconnect, and I/O subsystems, then build the diagnostics, automation, and observability needed to find issues quickly. This role sits at the center of silicon, firmware, platform, systems, and workload teams. You will turn hardware specifications and performance targets into an end-to-end bringup plan, drive cross-functional debug, and establish the stress and regression infrastructure that makes each new platform reliable across operating environments. In this role, you will: Contribute to the end-to-end software bringup and validation strategy for new silicon and first-party systems. Define software-driven test coverage across compute, memory, interconnect, I/O, and their system-level interactions. Build diagnostics, test automation, telemetry, and regression infrastructure that accelerate first-silicon learning and issue isolation. Lead bringup from initial silicon arrival through board and system integration, docking, runtime enablement, and model execution. Design stress tests that characterize reliability, performance, and stability across workloads and operating conditions. Translate architecture specifications and performance models into measurable acceptance crit

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 dynamic optimization of our resources. Implement fault-tolerant and resilient design

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 Baseten is building its own GPU infrastructure for large-scale inference. As we move into large scale, high-density NVIDIA systems, the hardest failures are intermittent, cross-layer, and difficult to prove: RoCE congestion, InfiniBand stalls, ECN/DCQCN mis-tuning, bad optics, RNIC issues, host kernel stalls, GPU driver problems, and workload symptoms that look like network problems, but are not. We are hiring a Lead Software Engineer to build a first-class observability and root-cause analysis system for GPU fabrics. This is a hard distributed systems problem, not a dashboarding problem. The system will collect high-volume signals from switches, hosts, active probes, and inference services; reduce and correlate them in real time; understand topology and service ownership; and produce actionable diagnosis while an incident is still unfolding. This role sits at the boundary between networking and inference software. RDMA data paths, GPUDirect transfers, prefill/decode disaggregation, KV cache movement, request routing, and workload backpressure can all create fabric symptoms or hide real fabric failures. The goal is to tell an operator, quickly and with evidence, whether an incident is caused by the fabric, host, NIC, GPU, RDMA path, scheduler, or serving layer — and what to do next. EXAMPLE INITIATIVES Real-time telemetry engine — Build the ingestion, reduction, storage, and query path for high-cardinality fab

Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are designed to solve real-world business problems. We’re training and deploying frontier models for enterprises who are building AI systems. We believe that our work is instrumental to the widespread adoption of AI and we are looking for folks that want to be part of that. We obsess over what we build. Each one of us is responsible for contributing to increasing the capabilities of our models and the value they drive for our customers. Cohere is a team of researchers, engineers, designers, and more, who are all passionate about their craft. We are a global technology company headquartered in Toronto with key offices in London, New York City, San Francisco, Montreal, Paris, Berlin and Seoul. Join us! Why this team? The GPU Clusters team builds and operates the superclusters that train Cohere’s frontier models. We sit at the intersection of hardware, distributed systems, and AI research. We work with cloud providers, researchers, and other infrastructure teams on problems few companies get to take on. As an Engineering Manager, you’ll lead a team of engineers who care deeply about GPU infrastructure. You’ll set technical direction, grow people, and help the company scale a rapidly growing compute footprint. As an Engineering Manager, you will: Hire, mentor, and grow a team of GPU infrastructure engineers , including performance, career development, and technical guidance on hard infrastructure problems Own the technical roadmap for the fleet: how we deploy, operate, and scale Kubernetes clusters, including workload scheduling, hardware fault detection, and performance Partner with researchers and ML engineers so the training and inference stack works well on new GPU architectures Work with cross-functional stakeholders such as Capacity, Finance, Legal, Security, and other infrastructure teams on planning, cost, compliance, an

About Sentry Software runs the world and the pace is faster than ever. Sentry helps developers fix errors and performance issues before users notice, so teams can spend less time firefighting and more time building. Trusted by 200,000+ organizations, Sentry is today’s application monitoring standard and our team is building its AI-native future. About the role Sentry provides developer-first observability to over 4 million developers worldwide. The Events Analytics Platform (EAP) team is at the heart of that mission: it powers how all of Sentry's event data, such as errors, transactions, spans, profiles, replays, and metrics, is stored, queried, and analyzed. It also powers Sentry's latest AI push, Seer. The EAP team makes it possible for developers to efficiently search and debug across massive volumes of data, providing the context needed to understand and fix issues quickly. This team is also a cornerstone of Sentry's long-term strategy to become a context assembly and telemetry platform that unifies different signals so developers can see the complete picture. As an engineering manager on the EAP team, you will lead a group of engineers building and scaling one of Sentry's most critical data platforms. You will be responsible for driving architectural evolution, ensuring system stability, and mentoring a talented team. This is a highly visible leadership role with direct ties to Sentry's long-term product and platform strategy. What you'll do Grow and develop a team of engineers with high expectations for ownership and impact Set the technical and strategic direction for the team, balancing short-term stability with long-term architectural evolution Drive development of core EAP features, including support for complex analytical queries, dynamic routing logic across fidelity levels, storage and compute separation, and modern patterns for analytical storage Ensure EAP can support the workload demands of AI agents and MCP servers that unlock new AI capabilities fo

About the Team Security is at the foundation of OpenAI's mission to ensure that artificial general intelligence benefits all of humanity. The Identity Infrastructure Engineering team sits at the core of this effort, designing and building the identity and access management solutions that protect model weights, customer data, and critical systems across multiple cloud environments. The team partners across OpenAI, including Applied Engineering, Research, IT, Security, Infrastructure, and Engineering, to provide secure and scalable platforms for identity, access management, permissioning, orchestration, and safe AI research. About the Role We’re looking for an engineering leader to lead Identity Infrastructure Engineering, the team building the systems that govern and scale access across OpenAI’s research, engineering, and internal platforms. This role sits at the center of cloud infrastructure, identity, software engineering, and security-critical operations. You’ll lead engineers building control planes, policy systems, workload and agent authorization patterns, infrastructure-as-code, and operational foundations that help OpenAI move quickly while keeping access reliable, auditable, least-privileged, and safe under failure. The ideal candidate has led teams responsible for large-scale, mission-critical infrastructure. They can go deep into code and architecture when needed, while giving engineers and technical leads the clarity and ownership to do their best work. They set technical direction, grow strong teams, make durable architecture decisions, and turn ambiguous 0-to-1 problems into platforms OpenAI can trust and build on for years. In this role, you will: Build and lead a high-performing Identity Infrastructure team, going deep enough technically to set direction while empowering the team to own delivery. Define the strategy for identity platform as the policy plane for access across people, agents, workloads, services, clouds, and internal systems. Scale Acc

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 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 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