Hardware Systems Engineer - AI Hardware

Cloudflare · Hybrid · €54,000-68,000 · hybrid We need to make thoughtful infrastructure choices affecting a significant portion of the Internet. Hardware we work with includes GPUs, servers and components, as well as PDUs and network hardware. As a Hardware Systems Engineer, you will work with colleagues on the Engineering teams, Product and Performance teams, and Hardware Sourcing teams to design, qualify and maintain Cloudflare's worldwide fleet of GPU servers. Responsibilities: Contribute to the technical requirements and end-to-end delivery of AI infrastructure , compute, networking, storage, power, and cooling , not just the accelerator Evaluate, select, and qualify AI hardware platforms (GPUs, custom ASICs, SmartNICs, storage) based on real workload requirements and first-principles analysis Design and validate rack-scale GPU systems: multi-node topologies, high-speed interconnects (NVLink, InfiniBand, RoCE), power distribution, and thermal management Run hands-on qualification: benchmarking, stress testing, failure mode analysis, and vendor RCA , you close the loop yourself Assess and qualify ODM/OEM server platforms; engage directly with vendors and work through the full technical qualification cycle Translate AI product and workload requirements into precise infrastructure specifications Identify gaps in the existing infrastructure stack and drive solutions across hardware, firmware, software, and operations Stay ahead of the AI hardware landscape , new silicon, new interconnects, new form factors , and bring informed, opinionated recommendations Build tooling and automation to support qualification workflows, performance analysis, and ongoing operational visibility Communicate your results and updates through blog posts and internal talks Requirements: Bachelor's, Master's, or PhD degree in Computer Engineering, Electrical Engineering, or Computer Science Experience in AI infrastructure, systems engineering, or hardware platform engineering First-principles understanding of AI accelerator architecture: compute pipelines, memory hierarchy (HBM, GDDR), interconnect topology, and/or how workload characteristics map to hardware capabilities Hands-on experience qualifying AI server platforms , you've run NCCL tests, profiled collective operations, debugged NVLink errors, and chased down PCIe lane misconfigurations Understand rack-scale systems: high-density power (kW/rack, busbar, PDU), liquid cooling (rear-door, direct liquid, immersion), high-speed networking infrastructure, and/or physical layer constraints Experience with AI/ML frameworks (vllm, sglang) at the systems level , you understand what they demand from the hardware and where bottlenecks actually live Familiarity with AI server form factors: HGX, OAC, OAM, UBB, open rack standards, and the tradeoffs between them Scripting and automation skills (Python, Bash, Go and Linux sysadmin); you build tooling to support your own work and the team's Strong written communication , you can write a rigorous technical specification and a crisp vendor requirements document Knowledge of performance benchmarking ; Previous experience in testing, measuring, and/or simulating hardware performance and an understanding of no-stone-left-unturned experimentation Knowledge of Redfish, IPMI and server remote management protocols, and experience with firmware updates Benefits: Medical/Rx Insurance Dental Insurance Vision Insurance Flexible Spending Accounts Commuter Spending Accounts Fertility & Family Forming Benefits On-demand mental health support and Employee Assistance Program Global Travel Medical Insurance Short and Long Term Disability Insurance Life & Accident Insurance 401(k) Retirement Savings Plan Employee Stock Participation Plan Flexible paid time off covering vacation and sick leave Leave programs, including parental, pregnancy health, medical, and bereavement leave