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River AI Inc.

Physical Design Engineer, Hardware

Palo Alto, California, United States +1

Location
Palo Alto, California, United States · Austin, Texas, United States
Work
Not stated
Employment
Not stated
Level
Senior
Function
Engineering
Pay
$200K – $420K a year (read from the ad)
Posted
5 months ago

Pay and the market here

The top of this role’s range, $420K a year, is 79% above the median of $235K for senior engineering jobs in Palo Alto (middle half $200K – $280K, 139 jobs that state pay).

577 engineering jobs open in Palo Alto: 5% remote, 139 posted in the last 30 days.

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About the role

At River, our mission is to create personal AI owned and shaped by each individual. To achieve this, we are rewriting the entire stack from scratch: personal hardware for local inference, bespoke training infrastructure, next-generation UIs, and frontier deep learning research.

Who we are

We are scientists, engineers, and builders from the industry's top tech companies and AI labs. We bring a proven track record of scaling consumer systems for hundreds of millions of users and architecting the pre-training infrastructure behind today's frontier models.

About the Role

We are looking for exceptional physical design engineers to transform our high-performance architectural concepts into production-ready silicon. You will own the physical implementation flow from synthesis through tape-out, pushing the absolute limits of advanced foundry nodes to maximize PPA. You will take ownership of block-level and top-level physical design, collaborating tightly with RTL designers to close timing, electrical, and physical verification for our custom AI accelerator.

What You’ll Do

  • Drive Synthesis and Place-and-Route: Own the physical implementation flow from RTL synthesis through placement, clock tree synthesis (CTS), and routing for high-performance blocks.
  • Maximize PPA: Optimize layout topologies to maximize cell density and utilization, architecting robust power delivery networks (PDN) to minimize IR drop and meet aggressive frequency targets on advanced foundry nodes.
  • Close Timing & Electricals: Conduct static timing analysis (STA), fix setup/hold violations across complex clock domains, and resolve signal integrity (SI), electromigration (EM) and IR-drop constraints.
  • Execute Physical Verification: Run and debug sign-off physical verification, including Design Rule Checking (DRC), Layout Versus Schematic (LVS), and Antenna rule compliance.
  • Co-Design with RTL: Partner directly with the RTL team to provide early physical feedback on logic structures, pipeline depth, and routing congestion to streamline implementation closure.
  • Advance Flow Automation: Integrate and develop next-generation AI-driven EDA tools and workflows to fundamentally accelerate the physical implementation cycle and optimize design closure.

Skills and Qualifications

Minimum Qualifications

  • Bachelor’s degree in Electrical Engineering or Computer Engineering, and 5+ years practical industry experience working with advanced process nodes (7nm or below).
  • Deep hands-on proficiency with industry-standard physical design, timing, and sign-off tools (e.g., Innovus, Fusion Compiler, PrimeTime, RedHawk).
  • Proven track record running logic synthesis, integrating compiled memory macros, and managing multi-voltage design techniques using power intent specifications (UPF/CPF).
  • Exceptional debugging skills with a first-principles approach to navigating complex trade-offs between congestion, timing slack, and power density in highly utilized designs.
  • A highly collaborative mindset and a bias for action to push boundaries and co-design effectively with RTL and architecture teams.

Preferred Qualifications: (We encourage you to apply even if you don't meet all of these)

  • An extensive track record of delivering high-performance SoCs, CPUs, GPUs, or AI accelerators through multiple successful production tape-outs.
  • Hands-on experience optimizing physical layouts for highly parallel compute structures, such as systolic arrays, large tensor execution units, or high-bandwidth memory (HBM) interfaces.
  • Experience custom-scripting or extending EDA tools (using Tcl, Python, or specialized ML APIs) to automate physical design closure and build bespoke workflow pipelines.

Logistics

  • Location: This role is based in Austin, Texas or Palo Alto, California.
  • Compensation: Depending on background, skills, and experience, the expected annual salary range for this position is $200,000 - $420,000 USD, plus equity.
  • Visa Sponsorship: We sponsor visas and are committed to supporting the process for the right candidate.
  • Benefits: River AI offers generous health, dental, and vision benefits, unlimited PTO, and relocation support as needed.

Source

Posted by River AI Inc. on their own hiring page, job-boards.greenhouse.io. OptiTalent shows it as published, read 07 Nov 2026 11:26 UTC; the original is the reference.

View the original ad ↗

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