Drimva

Google

Staff Hardware Engineer, Electrical Engineering Design, Google Cloud

Sunnyvale, CA, USA · Staff · Full-time · Posted Oct 22, 2026

Experience
6 years in electrical engineering design and 3 years in technical leadership; preferred: 8 years in board design, system architecture, and electrical engineering design.
Education
Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.

About the job

Leads architecture and electrical board design for next-generation Google Cloud infrastructure platforms, from system validation through high-volume manufacturing.

What you'll do

  • Set system architecture, technology roadmaps, board-level design direction, and design standards.
  • Lead cross-disciplinary design trade-offs and define interconnect, stackup, routing, power delivery, and high-speed signal guidelines.
  • Oversee validation, system bring-up, and debugging; lead cross-functional delivery and manufacturing initiatives.

What they ask for

  • Bachelor's degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
  • 6 years of experience working on electrical engineering design.
  • 3 years of experience in technical leadership.
  • Experience with Machine Learning (ML) and Artificial Intelligence (AI) Hardware platforms, including Graphics Processing Units (GPUs) and Tensor Processing Units (TPUs).

Nice to have

  • PhD degree in Electrical Engineering, Computer Engineering, Physics, a related field, or equivalent practical experience.
  • 8 years of experience working on board design, system architecture, and electrical engineering design; experience with data center engineering, AI/ML, server, storage and networking products.

Pay

$188000 - $274000 (USD) base salary

Tools

Machine Learning (ML), Artificial Intelligence (AI), Graphics Processing Units (GPUs), Tensor Processing Units (TPUs)

AI focus

Experience with AI/ML hardware platforms; the role designs infrastructure platforms for AI/ML workloads.

Model-written summary · the original posting is authoritative

First seen Oct 22, 2026 · Last verified Nov 5, 2026 (UTC)