Drimva

Amazon

Senior Hardware Development Engineer, Cloud AI/ML Server Team

$159K–$248K

Seattle, WA +2 · Senior · Full-time · Posted Aug 27, 2026

Location
Seattle, WA
Denver, CO
Cupertino, CA
Experience
7+ years of hardware design and development; preferred qualifications include 5+ years working with ODMs and 5+ years in hardware bring-up, debug, and root cause analysis.
Education
Bachelor's degree in electrical engineering, computer engineering, or equivalent.

About the job

Defines and develops GPU-accelerated server hardware for AI/ML workloads, from architecture and design through validation, production ramp, and fleet quality operations.

What you'll do

  • Define server architectures, designs, and component specifications; lead design reviews with ODM/JDM partners.
  • Develop and execute hardware validation, bring-up, debugging, and root-cause analysis through server and rack integration.
  • Own post-launch fleet quality metrics and drive corrective actions and design improvements using operational data.

What they ask for

  • Bachelor's degree in electrical engineering, computer engineering, or equivalent.
  • Experience developing functional specifications, design verification plans, and functional test procedures.
  • 7+ years of hardware design and development experience for server, compute, or large-scale infrastructure platforms.
  • Experience in at least one server technology area and leading hardware development through the full product lifecycle, from concept through production ramp.

Nice to have

  • Master's degree or PhD in Electrical Engineering, Computer Engineering, or a related field.
  • Experience with ODMs through development and manufacturing, high-speed bus/signal integrity or power delivery, hardware debug, fleet quality, or thermal/mechanical design.

Pay

USD 183,000.00 - 247,600.00 annually (base salary); USD 159,200.00 - 215,300.00 annually (base salary)

Tools

PCBA, PCIe, NVMe, GPU, EVT, DVT, PVT, ODM/JDM

AI focus

Designs and validates GPU-accelerated server hardware for AI/ML training and inference at cloud scale.

Model-written summary · the original posting is authoritative

First seen Oct 15, 2026 · Last verified Nov 5, 2026 (UTC)