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DensityAI

PCB Layout Engineer

Mountain View, California, United States

Location
Mountain View, California, United States
Work
Not stated
Employment
Not stated
Level
Not stated
Function
Engineering
Pay
$150K – $215K a year
Posted
3 months ago

Pay and the market here

The top of this role’s range, $215K a year, is 14% below the median of $250K for engineering jobs in Mountain View (middle half $215K – $284K, 640 jobs that state pay).

678 engineering jobs open in Mountain View: 4% remote, 151 posted in the last 30 days.

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About the role

About the role

Own the board-level physical design that turns our accelerator silicon into systems. You'll take high-speed, high-power designs from placement through fabrication release — defining stackups, escaping large fine-pitch BGAs, routing multi-hundred-amp power delivery, and holding the constraint discipline that lets a channel close margin in the lab and not just in simulation. You'll work at the seam where the package meets the system, partnering with signal and power integrity, packaging, and hardware systems, and directly with the fabrication and assembly partners who build what you release. When a board comes back and something doesn't behave, you're one of the people who knows why.

What will you do

  • Own board-level physical design for the systems our AI accelerators ship in stackup and impedance definition, placement, high-speed routing, and fabrication and assembly release packages
  • Own high-current power delivery layout and large fine-pitch BGA escape for advanced accelerator packages
  • Drive DFM/DFA with PCB fabrication and contract manufacturing partners, and support board bring-up and debug
  • Use and develop AI assisted tool flows to accelerate layout, review, and design-rule checking

What we're looking for

  • Exceptional abilities in constraint-driven layout of complex high-speed, high-current boards: controlled impedance and stackup definition, return-path and crosstalk management, length and skew matching, and via optimization
  • 8+ years of PCB layout experience on server, networking, or accelerator-class systems at high layer counts
  • Hands-on with industry-standard layout tools (Cadence Allegro, Siemens Xpedition, Altium, or equivalent) and release formats (Gerber, ODB++, IPC-2581)
  • Demonstrated ability to work closely with signal-integrity, power-integrity, packaging, and hardware systems teams to implement and close complex constraint sets across package and board
  • (Optional) 2.5D / 3D and multi-die package interfaces (CoWoS, EMIB, chiplets, HBM), rigid-flex or backplane design, CAD automation scripting, IPC CID / CID+, or overseas PCB fabrication and PCBA partner management

Full compensation packages are based on candidate experience and relevant certifications.

California pay range

$150,000—$215,000 USD

Compensation

Final offers depend on level, location, and skills relevant to the role. Additional compensation: equity grant per company guidelines; medical / dental / vision; 401(k); standard PTO.

Visa Sponsorship

DensityAI sponsors qualified candidates for H-1B, O-1, TN, E-3, and other employment-based visas, and we welcome applicants on F-1 OPT and STEM-OPT. Work authorization is required at start; we provide immigration support to secure or transfer status.

Export Controls

Aspects of this role may involve access to information subject to U.S. export controls (EAR/ITAR). We may discuss licensing or scope adjustments during the interview.

Equal Opportunity

DensityAI is an Equal Opportunity Employer. We do not discriminate on the basis of race, color, religious creed, national origin, ancestry, physical or mental disability, medical condition, genetic information, marital status, sex, gender, gender identity, gender expression, age (40+), sexual orientation, military or veteran status, pregnancy, or any other status protected by law. We comply with the California CROWN Act and provide reasonable accommodations on request.

Source

Posted by DensityAI on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 11:24 UTC; the original is the reference.

View the original ad ↗

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