Hardware / Machine Design Engineer
$150,000–$200,000 year
HybridBellevue, Washington, United States
Job Summary
Lead the design and configuration of GPU servers and rack-scale infrastructure using vendor reference architectures from NVIDIA, AMD, and emerging AI hardware providers. Partner with ODMs and OEMs to develop, validate, and optimize custom hardware platforms for production deployment, while owning rack-level architecture including mechanical layout, power distribution, thermal design, and cable management. Evaluate new GPU platforms and server technologies to determine suitability for next-generation AI workloads, balancing performance, reliability, manufacturability, and total cost of ownership. Support hardware validation, qualification, and production readiness for large-scale deployments, helping establish engineering standards and design best practices. Collaborate with data center, networking, and operations teams to ensure seamless integration across facilities.
Required Qualifications
- Extensive experience designing GPU-based servers, rack infrastructure, or large-scale compute platforms
- Deep knowledge of GPU server architecture and vendor reference designs, particularly NVIDIA and AMD ecosystems
- Experience working directly with ODMs and OEM partners to design, customize, qualify, and manufacture production hardware
- Strong understanding of rack-level infrastructure, including power, cooling, airflow, mechanical integration, cable management, and serviceability
- Experience supporting hyperscale cloud, AI infrastructure, HPC, or large-scale data center environments
- Ability to evaluate architectural trade-offs across performance, scalability, reliability, and cost
- Comfortable operating as a senior technical leader within a fast-moving, high-growth engineering organization
- U.S. work authorization
- Hybrid role based in the Bellevue, WA area
- Approximately three days per week in the office
- Candidates elsewhere in the U.S. who are open to relocation
Desired Qualifications
- Experience designing infrastructure supporting AI training clusters or large-scale inference platforms
- Experience with liquid cooling technologies, high-density rack deployments, or advanced thermal management
- Familiarity with multiple GPU generations and evolving accelerator technologies
- Background designing hardware platforms for cloud providers, hyperscalers, or AI infrastructure companies
- Experience influencing long-term hardware architecture and infrastructure strategy
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