Hardware Tools Engineer in San Francisco

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 member of the Capacity Strategy & Operations team, you will sit at the intersection of supply intelligence, demand forecasting, and cross-functional execution, turning a complex, fast-moving hardware market into a predictable, reliable foundation for our customers and internal engineering teams. This is not a purely analytical role. You will own the end-to-end capacity planning process: from translating customer commitments and growth forecasts into concrete supply requirements, to coordinating fulfillment across vendors, finance, and the infrastructure team, to building the systems that make all of this repeatable and scalable. When supply is constrained and tradeoffs are unavoidable, you are the person in the room who can model the options, make a clear recommendation, and drive alignment fast. You are a strong fit if you have operated at the intersection of strategy and execution before — someone who is equally comfortable building a capacity model in a spreadsheet and running a cross-functional war room when a customer deployment is at risk. EXAMPLE INITIATIVES Demand-Supply Alignment Framework: Build and own the process that translates customer pipeline, signed commitments, and growth projections into a forward-looking GPU demand signal — so the team is never caught flat-footed when a customer scales faster than expected. Constrained Allocation Playbook: Define the decision framework for how Basete

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 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 Delivery Director, Capacity programs for our on-premises data center builds and neo cloud (GPU cloud) delivery programs. This is a high-visibility, execution-critical role sitting at the intersection of infrastructure engineering, capacity planning, vendor/partner management, and customer delivery. You will own the end-to-end delivery lifecycle for large-scale compute infrastructure — from initial site/capacity commitments through power, networking, and hardware bring-up, to production-ready GPU/compute capacity landing in the hands of internal teams or customers. You'll be the person who turns ambitious infrastructure roadmaps into predictable, on-time, delivery. RESPONSIBILITIES Own delivery of on-prem infrastructure builds — colocation expansions, power/cooling readiness, rack-and-stack, network fabric bring-up, and hardware acceptance testing — coordinating across colo providers and partners, network engineering, hardware ops, and vendor teams. Drive neo cloud delivery programs — manage capacity delivery from GPU cloud and neo cloud partners (e.g., colocation/bare-metal/GPU cloud providers), including contract milestones, capacity ramps, SLAs, and go-live readiness. Build and maintain master delivery schedules across concurrent, multi-site, multi-vendor programs, integrating power/shell timelines, hardware lead times, logistics, and software/platform readiness into a single critical path.

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. Product at Baseten Product at Baseten is a nascent function. Our company today has a strong engineering culture, is heavily customer-obsessed, and moves fast. We're building the product function now, and you'd be one of the first people who will help define it. You'll work directly with our founders and with some of the best systems and infrastructure engineers in the world, and you'll set the standard for building great AI Infrastructure. PMs at Baseten don't sit above engineers - you earn ownership by being technical, finding the truth in front of customers, building great cross-functional relationships, and shipping great product experiences. The role Getting a model into production still takes real expertise — choosing a serving engine, sizing hardware, tuning it, wiring it into an app. We want a developer to go from "it runs on my laptop" to "it's serving production traffic" in minutes, on their own. You'll own the entire experience a developer touches to deploy and iterate: the CLI and SDKs, the console, onboarding, model discovery, deployment configuration, truss, and the increasingly agent-driven ways developers build. Your job is to make Baseten synonymous with Great DevEx and make it effortless to drive and self-serve deploy models on Baseten for far more developers than it is today. Impact and outcomes you'll drive You will collapse time-to-production — take a developer from first sign-up to a running, maint

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 We are looking for an IT Support / Operations Engineer to join Baseten as we continue to scale our IT team. In this role, you will play a critical part in bringing our technical support entirely in-house to provide a seamless, high-touch experience for all Baseten employees. As we continue to scale, you will be the primary point of contact for day-to-day technical issues, allowing you to have a direct impact on our team's productivity and overall office environment. This position is ideal for a hands-on problem solver who enjoys a mix of hardware and software troubleshooting, user lifecycle management, and maintaining the physical IT infrastructure of a modern office. While you will focus heavily on elevating our internal support standards, you will also assist with systems administration and workflow automation as our company evolves. This is a hybrid role based out of our San Francisco or New York office, following our standard policy of three days per week in-person to ensure our physical office and AV systems remain high-performing and reliable. RESPONSIBILITIES Serve as the escalation point for day-to-day technical support, diagnosing and resolving hardware and software issues across our Mac and Windows fleet Manage user lifecycle administration including provisioning, deprovisioning, and access management across all systems and services Own the IT onboarding experience for new employees — from laptop set

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

What you’ll do Execute weekly system-level exploratory testing across the scanner and supporting software; log and triage issues with clear reproduction steps. Work with engineering to debug root cause and validate fixes. Help maintain the DHF and traceability between user needs, design requirements, tests, and results. Own practical test execution logistics (fixtures, test data, environments, calibration artifacts) and keep things repeatable. Help build the continuous testing strategy: automated tests where feasible, plus structured manual and system tests. Support V&V activities, including coordination with external partners as needed. What we’re looking for Strong hands-on testing instincts for complex electromechanical systems with substantial software. Ability to write clear bug reports and communicate risk/impact. Experience building and maintaining test plans/protocols; comfort operating lab equipment and debugging across layers. Useful experience Experience testing complex systems end-to-end (automation where it pays off, plus hands-on hardware/instrumentation). Medical device or other safety-critical environments and comfort translating risk into practical test coverage.

What you’ll do Be the generalist EE for the scanner system: integration, bring-up, debugging, and making the electrical side of the device reliable and serviceable. Own ultrasound experimentations that feeds the image reconstruction team Design and execute experiment setups for transducer characterization (element sensitivity, bandwidth, cross-talk mapping, beam profile measurements) and ex vivo / phantom clinical testing. Acquire, process, and analyze RF and baseband signals for data quality assessment and benchmarking. Design simple boards and adapters as needed (monitoring, power/safety, interface/conditioning), and take them from prototype through a stable revision. Prototype quickly, then harden what works: wiring/harnessing, grounding, safety interlocks, and reliable integration across subsystems. Own practical test setups and documentation (fixtures, scripts, procedures) that make experiments repeatable and results comparable over time. What we’re looking for Strong hands-on EE background with experience building, debugging, and iterating on real systems in the lab. Solid understanding of signal processing fundamentals — knows what to measure, how to condition and digitize it, and how to evaluate signal quality in the context of an imaging system (SNR, bandwidth, dynamic range, artifacts). Comfortable spanning system integration + occasional design work (schematics/layout reviews or light PCB design) in a fast-moving environment. Ability to work at the boundary between hardware and algorithms: measure reality, communicate constraints, and help close gaps vs simulation. High agency and practicality: able to set up experiments, get trustworthy data, and unblock others on a lean team. Useful experience Analog/mixed-signal, or high-speed data capture experience; strong instincts for instrumentation and noise/debugging. Ultrasound or acoustic sensor handling: hydrophone calibration and field mapping, transducer impedance characterization, element-level sensitivity

What you’ll do Own day-to-day operations for the scanner program and scanner builds in the spa: purchasing/procurement, vendor management, receiving, inventory, and logistics. Stand up lightweight production operations as we move from prototypes to repeatable builds: build planning, kitting, work instructions, and readiness checklists. Partner with Quality to ensure the operational system supports compliance: traceability, document control, training records, NCR/CAPA workflows, and audit readiness. Drive cross-functional execution for the physical spa build-out and scanner integration: schedules, dependencies, risk register, and weekly coordination with vendors and internal teams. Own the “integration glue” across facilities + device ops: commissioning plans, acceptance criteria, and operational handoff (runbooks, maintenance, spares, escalation paths). Build and track operational metrics: cost, budget, lead times, vendor performance, build throughput, and reliability of critical subsystems. Audit of import/export documentation, management of contract renewals, regulatory compliance. What we’re looking for Proven operations leadership in hardware/medical/robotics (or similarly complex electromechanical products), including procurement and vendor management. Strong program management instincts: can run schedules, unblock cross-functional dependencies, and keep priorities clear under ambiguity. Comfort operating in quality/regulatory environments and building processes that are rigorous without slowing a small team. High ownership and bias to action: can jump between spreadsheets, docks, and the lab/site to keep the program moving. Useful experience Experience running prototype-to-production transitions (NPI, EVT/DVT/PVT-style builds, CM/EMS collaboration). Facilities / construction operations experience (GC coordination, MEP commissioning, site readiness). Familiarity with inventory systems and procurement tooling (even “simple but disciplined”).

What you’ll do Act as the in-house electrical lead for Midjourney Medical: own the electrical architecture of the scanner and the technical direction for all board-level design. Own complex board design end-to-end: architecture, schematic capture, layout (high-speed digital, analog/mixed-signal, power), DFM/DFT, fabrication and assembly vendor management, bring-up, and revision control. Write firmware for embedded targets (MCU/SoC): drivers, real-time control loops, safety-relevant logic, bootloaders, and field update paths. Audit and update HDL (FPGA) code for high-throughput data acquisition, timing/synchronization, triggering, and pre-processing of ultrasound and sensor data streams. Define electrical interfaces and data contracts with software, recon/ML and mechanical teams: timing budgets, clocking/sync, signal integrity, connectors/harnessing, and failure modes. Establish electrical engineering rigor: design reviews, schematic/layout review checklists, bring-up procedures, test fixtures, and documentation suitable for a regulated medical device program (DHF, traceability, change control). Mentor and grow the electrical function; select and manage external design partners where leverage is high. What we’re looking for Deep experience designing complex boards from blank page to stable revision, including high-speed digital and analog/mixed-signal domains. Strong schematic and layout skills (Altium/KiCad or equivalent) with real signal integrity, power integrity, grounding, and EMI/EMC instincts. Solid embedded firmware background in C/C++ (and Python for tooling): peripherals, DMA, interrupts, real-time constraints, and debugging on hardware. Practical HDL experience (VHDL/Verilog/SystemVerilog) for data acquisition, timing, and streaming interfaces. Track record of owning bring-up and debug on real hardware: scopes, logic analyzers, and disciplined root-cause analysis. Technical leadership: clear trade-offs, strong written documentation, and the ability to set

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 Flexport: At Flexport, we believe global trade can move the human race forward. That’s why it’s our mission to make global commerce so easy there will be more of it. We’re shaping the future of a $10T industry with solutions powered by innovative technology and exceptional people. Today, companies of all sizes—from emerging brands to Fortune 500s—use Flexport technology to move more than $19B of merchandise across 112 countries a year. The recent global supply chain crisis has put Flexport center stage as we continue to play a pivotal role in how goods move around the world. We are proud to have the support of the best investors in the game who believe in our mission, solutions and people. Ready to tackle global challenges that impact business, society, and the environment? Come join us. Help Win New Business The Opportunity: We are scaling our dedicated Data Center practice, and we are looking for the person who will lead it. This is a founding commercial role. You will start as a team of one, owning the full sales motion end-to-end, and you will build the team around you as the practice grows. You will define how Flexport goes to market with hyperscalers, hardware OEMs, and the broader ecosystem. You will set the playbook, win the first marquee accounts, and hire the people who scale what you build. Reporting directly to the Regional General Manager, you will operate with a high degree of autonomy and direct access to executive leadership. This role features a 50/50 compensation model (Base + Uncapped bonus, with accelerators), with OTEs of $350k+, designed for strong leaders who take bets on themselves. Why This Role Is Different: The data center logistics market is not a standard freight problem. A single AI compute rack can cost more than $1 million and weigh up to 4,000 pounds. Racks contain Class 9 dangerous goods (lithium-ion batteries) and liquid cooling systems requiring specialized handling. Construction sequencing failures delayed 57% o

About the Team OpenAI’s Legal team plays a crucial role in advancing our mission by tackling innovative and fundamental legal issues in AI. The team includes professionals from diverse legal fields—technology, AI, infrastructure, privacy, IP, corporate, employment, tax, regulatory, and litigation—who collaborate closely with colleagues across the company. If you are passionate about being a technology lawyer working on cutting-edge challenges, you’ll thrive here. About the Role We’re seeking a senior lawyer to participate in commercial legal strategy and execution across OpenAI’s fast-growing infrastructure portfolio. This is a cross-functional role that will partner closely with procurement, supply chain, partnerships, finance, and product teams to structure, negotiate, and manage the transactions that will support OpenAI’s long-term infrastructure ambitions. We’re looking for an experienced infrastructure transactions lawyer who thrives in ambiguity and wants to help define the commercial playbook for infrastructure efforts in the AI era. This role reports to the Associate General Counsel for infrastructure. 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: Own commercial legal strategy and risk management for OpenAI infrastructure transactions. Draft, negotiate, and advise on complex agreements with infrastructure suppliers, manufacturers, distributors, and technology partners. Support strategic partnerships involving AI infrastructure and hardware supply chains. Develop frameworks for procurement, licensing, and collaboration across the infrastructure ecosystem. Partner with finance and operations teams to align contract terms with business and compliance requirements. Collaborate with policy and regulatory colleagues on issues impacting global supply chains, export controls, and manufacturing. Build scalable, efficient contracting process

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 is building the infrastructure foundation for the next generation of AI. The Data Center Engineering team defines the strategy, reference architectures, technical requirements, and delivery standards for the large-scale data centers that support OpenAI research, products, and infrastructure partners. As a Data Center Infrastructure Electrical Engineer, you will help define, validate, and scale the electrical power systems that support high-density AI compute. You will translate evolving compute requirements into practical facility and rack-power architectures, evaluate new technologies and vendor solutions, and drive technical decisions across design, manufacturing validation, construction, commissioning, deployment, and operations. This role is best suited for a senior hands-on engineer with deep experience in mission-critical power systems, strong judgment under ambiguity, and the ability to connect facility infrastructure, hardware requirements, controls, telemetry, reliability, and operations. About the Role We are seeking a senior electrical infrastructure engineer to lead the development of reliable, scalable, and efficient power architectures for high-density, liquid-cooled AI data centers. The ideal candidate has strong practical experience with critical electrical systems at data centers or comparable industrial scale, including medium-voltage and low-voltage distribution, utility interfaces, backup power, UPS and battery systems, rack power delivery, grounding, protection, controls, and monitoring systems. You should be comfortable moving between long-range architecture, detailed engineering review, lab validation, vendor qualification, field deployment, and operational troubleshooting. Key Responsibilities Design and optimize electrical topologies and equipment strategies that reduce cost, accelerate schedules, improve efficiency, increase scalability, and maintain high reliability and maintainability. Review and develop basis-of-des