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Silicon Engineer, Power Analysis

Google DeepMind · Mountain View, CA, USA

CHECKED 22H AGO

Frontier labonsitesenior$217k–$236k
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At a glance

Highlights

  • Develop custom silicon powering Google's direct-to-consumer products.
  • Architect advanced-node power solutions with block and full-chip budgets.
  • Define power management from SoC architecture through post-silicon validation.

Ideal candidate

Seasoned silicon power engineer who blends hardware insight with software automation and cross-functional leadership. Passionate about efficient custom silicon and pushing performance for products used by millions.

Requirements

  • 7 years of experience in ASIC power analysis & optimization including production chips
  • Experience in chip tape-outs
  • Experience interacting and collaborating with silicon foundries and external vendors for tapeout
  • Experience with Verilog and industry-standard EDA tools for power analysis & optimization
  • Experience with scripting languages (e.g., Perl, Tcl) for automation
  • Software development experience
  • Master's degree or PhD in Electrical Engineering, Physics or related field (preferred)

Lab profile

About Google DeepMind

Google's AI lab building frontier models like Gemini to advance science and general intelligence.

What they build

  • Gemini
  • Gemma
  • AlphaFold

Known for

  • Frontier foundation models and GenAI
  • Large-scale training with JAX, PyTorch, TensorFlow
  • Model evaluation and deployment expertise
  • Responsible frontier AI research

Key facts

  • Founded in 2010
  • Headquartered in London, UK
  • Part of Google (Alphabet)
More about Google DeepMind →
Apply on the lab’s site ↗