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Physical Design Engineer

Etched · San Jose

Infrastructureonsitesenior$200k–$375k
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At a glance

Highlights

  • Build hardware for frontier intelligence spanning chips, racks, and software.
  • Drive best-in-class throughput and latency across prefill and decode workloads.
  • Help redefine the infrastructure layer for the fastest-growing industry.

What they offer

  • Medical, dental, and vision packages with generous premium coverage
  • $500 per month credit for waiving medical benefits
  • Housing subsidy of $2.5k per month for those living within walking distance of the office
  • Relocation support for those moving to San Jose (Santana Row)
  • Wellness benefits covering fitness, mental health, and more
  • Daily lunch + dinner in office
  • Unlimited compute budget subject to ROI justification

Ideal candidate

A deeply creative physical design engineer with 5-10+ years of experience who thinks from first principles and thrives in fast-paced, in-person startup environments building frontier AI hardware.

Requirements

  • 5-10+ years experience with PD tools, flow and design methodology from RTL synthesis to GDSII sign-off
  • Experience with back-end design and timing closure on advanced process nodes (5nm and below)
  • Experience with Cadence (Innovus, Genus) or Synopsys (ICC2, Fusion Compiler) automated RTL-to-GDSII flows
  • Experience with sign-off tools (PrimeTime, Tempus, Voltus, etc.)
  • Experience with UPF-based low power design methodology, power verification, synthesis, scan insertion/ATPG, formal verification, floorplanning, placement, CTS, routing, IR drop, and EM/antenna analysis
  • Deeply creative and able to think from first principles
  • Familiarity with modern ML and LLM model architectures
  • Ability to program with Python or another scripting language
  • Familiarity with AI tools for programming/coding
  • Startup experience or comfort working in fast-paced environments
remote policy
fully in-person

Lab profile

About Etched

Building specialized AI chips and systems for frontier inference with best-in-class throughput and latency.

What they build

  • Sohu AI inference chip
  • AI racks and hardware systems
  • Inference software stack

Known for

  • Full-stack co-design of chips, racks, software and manufacturing
  • Best-in-class throughput and latency for prefill and decode
  • Inference-optimized architecture

Key facts

  • Backed by hundreds of millions from top-tier investors
More about Etched →
Apply on the lab’s site ↗

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