Physical Design Engineer
Etched · San Jose
Infrastructureonsitesenior$200k–$375k
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
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