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Physical Design Engineer

Job in Mountain View, Santa Clara County, California, 94039, USA
Listing for: Acceler8 Talent
Full Time position
Listed on 2026-09-14
Job specializations:
  • Engineering
    Hardware Engineer, Systems Engineer, Electronics Engineer
Salary/Wage Range or Industry Benchmark: 180000 - 280000 USD Yearly USD 180000.00 280000.00 YEAR
Job Description & How to Apply Below

I’m working with an AI compute startup rebuilding the hardware and software stack around extreme compute density.

The team is developing a tightly integrated platform spanning advanced silicon, packaging, firmware, compilers, kernels, and infrastructure. This is broader than a conventional accelerator project, with physical-design decisions directly affecting the architecture and performance of the complete system.

This role will own physical design for one or more blocks of a new AI accelerator, from initial floor planning through final sign-off.

You’ll work on problems such as:

  • Owning synthesis, floor planning, placement, routing, CTS, and sign-off
  • Closing timing, power, area, congestion, and physical-verification requirements
  • Developing AI-assisted flows to accelerate physical-design and sign-off timelines
  • Working with architects and RTL designers to resolve implementation trade-offs
  • Collaborating with EDA vendors, foundries, packaging, and verification teams
  • Delivering complex blocks through tape-out and first silicon.

Looking for engineers who have:

  • 8+ years of hands-on physical-design experience
  • Experience with high-performance designs at 7nm or below
  • Full-flow ownership from synthesis and floor planning through sign-off
  • Strong experience with Cadence Innovus, Synopsys Fusion Compiler, or equivalent
  • Hands-on timing sign-off experience using Prime Time, Tempus, or equivalent
  • Experience working closely with architecture, RTL, foundry, and EDA teams
  • A track record of taking complex silicon through tape-out.

Nice to have:

  • CoWoS, chiplet, 2.5D, or 3D packaging experience
  • Thermal, IR-drop, electromigration, or signal-integrity sign-off
  • Experience with AI accelerators, CPUs, GPUs, or other high-performance compute silicon
  • Experience building or improving physical-design automation.

This is an opportunity to own foundational implementation decisions for a new AI computing platform alongside engineers with experience across advanced CPUs, custom AI silicon, and wafer-scale systems.

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