Physical Design Engineer - Block Level, Subsystem Implementation
Etched · San Jose
Infrastructureonsitesenior$200k–$375k
At a glance
Highlights
- Own block-level implementation from synthesis through GDSII sign-off.
- Build frontier inference clusters co-designing chips, racks, and software.
- Drive PPA optimization for blocks powering best-in-class AI throughput.
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)
- Various wellness benefits covering fitness, mental health, and more
- Daily lunch and dinner in our office
- Unlimited compute budget subject to ROI justification
Ideal candidate
Creative, first-principles physical design engineer with 5-10+ years experience who thrives in fast-paced, in-person startup environments and cares about maximizing PPA for frontier AI hardware.
Requirements
- 5-10+ years of previous 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 (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
- Scripting ability in Tcl, Python, or Perl for flow automation and debug
- Deeply creative and able to think from first principles
- 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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