Lead ASIC Power Engineer for ML Accelerators

Anysilicon

Sunnyvale, Northern (CA, KY)

Hybrid

USD 185,000 - 250,000

Full time

5 days ago
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Job summary

Google in Sunnyvale, CA is seeking a Staff ASIC Power Engineer for ML Accelerators to drive power efficiency in advanced AI hardware. You will lead power modeling, architecture-level optimizations, and collaborate with software and system teams to meet dynamic power targets.

You should have a strong background in power design and SoC architecture, with leadership experience and a proven track record delivering complex projects end-to-end in a fast-paced environment.

Qualifications

  • Bachelor's degree in Electrical/Computer Engineering or related field; equivalent experience accepted.
  • 10 years of design or architecture experience in power-related domains.
  • Experience with power design, modeling, architecture or reduction methodologies.

Responsibilities

  • Contribute to design power modeling and converge to power targets.
  • Investigate, specify and deploy architectural and microarchitectural power optimization techniques.
  • Define best practices for low-power RTL designs.
  • Collaborate with cross-functional teams to create power management architectures meeting dynamic targets.
  • Lead power team to deliver complex projects end-to-end.

Skills

Power modeling
Technical leadership
Problem solving
DVFS & thermal management
Collaborative skills

Education

Bachelor's degree in EE/CE/CS
Master's or PhD in EE/CE/CS (preferred)

Tools

Power design tools
RTL power analysis
SoC design tools
Power modeling software

Job description

Google in Sunnyvale, CA is seeking a Staff ASIC Power Engineer for ML Accelerators to drive power efficiency in advanced AI hardware. You will lead power modeling, architecture-level optimizations, and collaborate with software and system teams to meet dynamic power targets.

You should have a strong background in power design and SoC architecture, with leadership experience and a proven track record delivering complex projects end-to-end in a fast-paced environment.

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