Hardware Operations Engineer in United States

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’s Model Performance (MP) team is responsible for ensuring the models running on our platform are fast, reliable, and cost‑efficient. As part of this team, you’ll focus on Model APIs — the infrastructure powering our hosted API endpoints for the latest open‑source models. This work spans distributed systems, model serving, and developer experience. You’ll join a small, high‑impact team operating at the intersection of product, model performance, and infra, helping to define how developers interact with AI models at scale. RESPONSIBILITIES: Design, build, and operate the Model APIs surface with focus on advanced inference capabilities: structured outputs (JSON mode, grammar-constrained generation), tool/function calling and multi-modal serving Profile and optimize TensorRT-LLM kernels, analyze CUDA kernel performance, implement custom CUDA operators, tune memory allocation patterns for maximum throughput and optimize communication patterns across multi-GPU setups Productionize performance improvements across runtimes with deep understanding of their internals: speculative decoding implementations, guided generation for structured outputs, custom scheduling and routing algorithms for high-performance serving Build comprehensive benchmarking frameworks that measure real-world performance across different model architectures, batch sizes, sequence lengths, and hardware configurations Productionize performa

What you’ll do Design and implement secure cloud pipelines that ingest very large scan datasets (multi-terabyte), reliably and resumably. Build orchestration for GPU-accelerated reconstruction and analysis with strong retry semantics, idempotency, and cost controls. Define end-to-end data lifecycle for medical imaging: raw vs intermediate vs derived artifacts, retention policies, and reproducibility. Implement security + compliance primitives appropriate for HIPAA/PHI: encryption in transit/at rest, key management, least privilege, audit logs, and access reviews. Build operational tooling: monitoring, alerting, runbooks, and incident-driven improvements for a growing device fleet. What we’re looking for Strong experience with cloud batch/queueing/orchestration, storage systems, and data pipeline reliability. Experience shipping production systems that handle large data volumes and failure-prone networks. Practical security mindset (least privilege, secrets, audit logging) and comfort operating in compliance-constrained environments. Useful experience Building reliable data pipelines at scale (queues/orchestration, resumable uploads, GPU batch execution) with strong observability. Security + privacy by default: encryption, least-privilege access, auditing, and practical HIPAA/PHI guardrails. Owning the “boring” backend details that keep a lean team moving: schemas/migrations, cost controls, retries, and runbooks. Understanding compute tradeoffs across hardware options, and specifying appropriate cloud resources.

About Us At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company. At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in. About the Role The Product Platform Tools team builds and operates Cloudflare's internal support and admin platform - the foundation that customer-facing and operational teams across the company rely on to do their jobs. As a Systems Engineer on this team, you'll design and build the backend services, infrastructure, APIs, and integrations that power this platform at enterprise scale, working closely with both engineering teams and non-engineering

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

About the Team 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 are operational in how we do our work, and are committed to supporting all products and research at OpenAI. Our Security team tenets include: prioritizing for impact, enabling researchers, preparing for future transformative technologies, and engaging a robust security culture. About the Role OpenAI is seeking a Security Engineer to join our Infrastructure Security (InfraSec) team. InfraSec protects the foundations of OpenAI’s research and production environments, spanning GPU supercomputing clusters, multi-cloud infrastructure, datacenters, networking, storage, and the critical services that power our frontier AI models. Our charter includes securing everything from bare-metal hardware and firmware, to Kubernetes clusters and service meshes, to data storage and access pathways for highly sensitive model weights and user data. In this role, you will: Design and build security controls across diverse layers (e.g., physical hardware, firmware/BMC, OS, Kubernetes, networks, and CI/CD) to defend against sophisticated adversaries and insider threats. Collaborate with engineering and security teams to drive deployment of security enhancements and control changes across broad-scale infrastructure. Tackle high-impact projects such as checkpoint encryption, network isolation, secret management, and machine identity, while continuously raising the security bar for emerging AI workloads. Take a generalist approach to building security controls, balancing a mix of security expertise and broad technical skillsets to adapt to evolving challenges. You will thrive in this role if you have: Deep understanding of security principles, best practices, and common vulnerabilities. A proactive mindset, with the ability to identify and address secu

Lead Design and Analysis Engineer (Electrical Systems Design) Company: The Boeing Company Boeing is currently hiring for a Lead Design and Analysis Engineer located in Berkeley, MO to be a part of the MQ-25 Electrical and Equipment Installation team. The MQ-25 Stingray is a new autonomous, unmanned carrier based refueling air vehicle. The selected candidate will be a part of aviation history by helping our Navy customer productization Autonomous Carrier landing, takeoff and refueling capabilities. The MQ-25 program is currently building the Engineering and Manufacturing Development (EMD) vehicles for the Navy. Additional work is under way for the beginning of the Low Rate Initial Production (LRIP) program for additional vehicles. The MQ-25 Electrical & Equipment team is responsible for the power architecture & design, electrical equipment technical management, electrical installation design, wire harness design, and integrating avionics and other equipment into the vehicle. This role will be focused on the power architecture & design. Position Responsibilities: Leads work with customers to develop and document complex electronic and electrical system requirements. Leads and coordinates work to analyze and translate requirements into system architecture, hardware and software designs and interface specifications. Leads work to test and validate to ensure system designs meet operational and functional requirements. Researches technology advances for potential application to company business needs. Makes recommendations for technology investments. This position is expected to be 100% onsite. The selected candidate will be require

Hyliion is committed to creating innovative solutions that enable clean, flexible and affordable electricity production. The Company’s primary focus is to develop distributed power generators that can operate on various fuel sources to future-proof against an ever-changing energy economy. Job Purpose The Senior Manager, Additive Fleet is responsible for the day-to-day performance of Hyliion's laser powder bed fusion (LPBF) printer fleet in Austin, which produces the complex, high-density metal heat exchanger hardware in the KARNO Core. This hardware can only be produced through metal additive manufacturing, so Hyliion's ability to build KARNO at scale depends directly on the health, uptime, and throughput of the fleet. The role leads the technicians and operators who run and maintain the machines, and owns preventive maintenance strategy, machine health monitoring, and decisions on hardware and software upgrades. The fleet runs the full range of Colibrium Additive LPBF platforms, including new machine technology being adopted in real time, and a primary focus is reducing machine-to-machine variation and building repeatable processes across machine models. This is a hands-on leadership role with regular time on the shop floor, and its scope will grow as Hyliion's print capacity scales. AI at Hyliion At Hyliion, AI is core to how we work. We equip every team member with leading AI tools and count on you to use them — to move faster, solve harder problems, and help us realize the full potential of KARNO technology for the world. Duties and Responsibilities Own fleet uptime and drive continuous improvement in machine-to-machine consistency across Hyliion's LPBF printer fleet. Build and maintain a preventive maintenance program across all machines to identify failure modes before they cause downtime. Lead, schedule, and develop the team of technicians and operators who run and maintain the fleet. Develop machine health monitoring us

Mechanical and Thermal Laboratory Technician Position Summary Graphcore is a globally recognized leader in Artificial Intelligence computing systems. The company designs advanced semiconductors and data center hardware that provide the specialized processing power needed to drive AI innovation, while delivering the efficiency required to support its broader adoption. As part of the SoftBank Group, Graphcore is a member of an elite family of companies responsible for some of the world’s most transformative technologies. We are opening a new AI Engineering Campus in Austin, which will play a central role in Graphcore's work building the future of AI computing. Responsibilities The Mechanical and Thermal Laboratory Technician is a hands-on technical role supporting the development and validation of advanced AI hardware systems for data center environments. Working as part of a cross-functional engineering team, this individual will be responsible for executing mechanical and thermal laboratory testing, supporting product validation activities, prototype fabrication and assisting with troubleshooting and root-cause analysis of complex hardware systems. Requirements Associate degree in Mechanical Engineering Technology or a related technical field preferred. Equivalent combinations of education, training, and relevant experience will be considered, including experienced non-degreed candidates or candidates with degrees in unrelated disciplines. Minimum of 5 years of experience working in mechanical laboratories, machine shops, test labs, or similar technical environments. Experience with server hardware platforms and data center equipment. Knowledge of Direct Liquid Cooling (DLC) systems and their implementation in server environments. Experience operating forklifts, pallet jacks, and other material-handling equipment. Key Responsibilities Execute mechanical and thermal test plans to validate hardware designs a

About the Team OpenAI’s Industrial Compute team is building and productizing infrastructure capabilities that help organizations deploy and operate advanced AI systems at scale. The team works across AI hardware, systems engineering, physical infrastructure, and customer delivery to turn emerging technologies into reliable, repeatable infrastructure solutions. Our work sits at the intersection of technical strategy, product development, engineering, and deployment. We partner closely with customers and internal engineering teams to solve complex infrastructure challenges spanning compute, power, cooling, controls, and facility efficiency. About the Role We are seeking a senior, hands-on Data Center Infrastructure Architect to develop and optimize the physical infrastructure required for large-scale AI deployments. This is a broad technical role spanning data center architecture, electrical and mechanical systems, high-density compute, controls, telemetry, and digital modeling. You will use simulation, operational data, and digital-twin approaches to evaluate infrastructure designs, identify system-level constraints, and improve efficiency, reliability, cost, and speed of deployment. The ideal candidate can move fluidly between first-principles analysis, facility and equipment design, computational modeling, engineering review, and real-world implementation. You should be comfortable working across disciplines rather than operating solely within electrical, mechanical, or software boundaries. Key Responsibilities Define system-level architectures for high-density AI data centers across power, cooling, IT equipment, controls, and facility infrastructure. Develop digital twins and other computational models that represent the behavior of data center systems under changing workloads, environmental conditions, equipment configurations, and failure scenarios. Use design and operational data to identify constraints, improve PUE and related efficiency metrics, and optimize

About the Team OpenAI’s Stargate and 3P Engineering teams are responsible for building and scaling the external infrastructure ecosystem that powers advanced AI systems. We work across hyperscalers, colocation providers, cloud partners, and strategic third-party operators to turn contracted capacity into production-ready compute. Our scope spans the full lifecycle of external deployments: commercial alignment, technical readiness, network integration, hardware enablement, operational readiness, and long-range scaling strategy. As OpenAI’s infrastructure footprint expands globally, we need leaders who can convert complex partner environments into reliable, high-velocity capacity for training and inference workloads. About the Role We are seeking a Technical Program Manager, Token-as-a-Service (TaaS) to lead delivery of external compute capacity that directly serves OpenAI model workloads. In this role, you will own complex cross-functional programs that transform third-party infrastructure into usable tokens at scale. You will partner across engineering, capacity planning, networking, hardware, finance, product, and external providers to ensure that deployed capacity translates into real production throughput. This role sits at the intersection of infrastructure execution, systems readiness, and business impact. Success requires strong technical fluency, elite program management, and the ability to drive accountability across internal teams and external partners. This is a high-visibility role with direct impact on OpenAI’s ability to scale model training and inference globally. This role is based in San Francisco, CA, with a hybrid work model of 3 days in office per week. Relocation assistance is available. Key Responsibilities Lead end-to-end delivery programs that convert external infrastructure capacity into production-ready token supply. Own readiness across compute, storage, networking, security, and operational dependencies for third-party environments. Build

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. ABOUT THE ROLE This role owns Baseten's relationships and market intelligence across the hardware and chip layer of the compute stack: NVIDIA directly and key OEM partners such as Dell, Lenovo, Pegatron, and Supermicro. As Baseten's compute strategy increasingly depends on hardware access and terms, this role is central to keeping Baseten ahead of the market. WHAT YOU'LL DO Build and maintain relationships across NVIDIA and key OEM partners (e.g. Dell, Supermicro) Track market intelligence on hardware availability, roadmaps, and terms to keep Baseten informed and strategically well-positioned Support deal structuring and negotiation in partnership with Baseten's deal-making function Work closely with Infrastructure and Hardware Platform engineering teams to ensure consistent, high-quality provider relationships and engineering partnerships Represent Baseten credibly across senior relationships in the hardware ecosystem, escalating to company leadership when strategically valuable WHAT WE'RE LOOKING FOR Existing relationships and credibility within the NVIDIA, OEM, and HPC ecosystem Strong relationship-management instincts, with the judgment to know when to bring in senior leadership for maximum impact Comfort operating in a fast-moving, high-stakes market where hardware access can be a major competitive differentiator Collaborative style — this role depends on close coordination with engineering counterparts, not just ex

Lead Analyst Company: The Boeing Company Boeing F-22 Mission Systems team is hiring for a Lead Analyst located in Berkeley, MO . As Lead Analyst, you will be responsible for analyzing engineering solutions for the F-22 Raptor, including both enhancing existing field units with the addition of new capabilities as well as architecting and testing completely new systems. In this role you will be joining a cross-functional team to progress our products through the development lifecycle. Position Responsibilities: Leads analysis and translation of complex requirements into system architecture, hardware and software designs and interface specifications. Must be able to work in a fast-paced, collaborative environment, engaging with multiple teams and being responsive to agile requirements and critical path customer need dates. Collaborates with Responsible Engineers, customer technical staff, suppliers, and Lockheed Martin teammates to develop and document complex electronic and electrical system requirements for F-22 avionics sub-systems and weapon system architecture Analyzes and translates requirements into system architecture, hardware and software designs and interface specifications in support of lab and operational environments Reviews test data, including off-nominal data, for accuracy, quality and/or fidelity prior to delivery to customer This position is expected to be 100% onsite. The selected candidate will be required to work onsite at one of the listed location options. This position requires the ability to obtain a US Secret Security Clearance for which the US Government requires US Citizenship A final Secret Clearance

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 This role owns Baseten's relationships and market intelligence across hyperscalers and strategic neoclouds, including NVIDIA cloud partners. This is a technical and commercial role in equal measure: you'll evaluate capacity from the GPU to the data center, negotiate cost and terms with suppliers, and stay close enough to the market to develop and defend a real point of view on where it's heading. Given current market conditions, Baseten needs a much stronger pulse on this part of the market so we can track pricing, stay close to the right relationships, and move fast the moment more capacity is needed. This is a senior, experienced hire who will also help pair with and develop 1-2 junior to mid-level teammates covering the same space. WHAT YOU'LL DO Build and maintain deep relationships across hyperscalers and strategic neoclouds (including NVIDIA cloud partners), working each organization from top to bottom rather than a single point of contact Maintain a consistent, "top of mind" presence with key accounts so Baseten is positioned to move quickly when capacity needs arise Evaluate capacity from the GPU to the data center — hardware generation, rack and node configuration, interconnect, power density, and cooling — so you know what a configuration will actually deliver, not just what the spec sheet claims Live in compute pricing daily: track rates by GPU generation, region, and contract term to keep Baseten inf

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