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Phinity Labs

Research Engineer - Hardware, Data

San Francisco, California, United States

Location
San Francisco, California, United States
Work
On-site
Employment
Full-time
Level
Not stated
Function
Data & AI
Pay
Not stated
Posted
4 weeks ago

Pay and the market here

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About the role

Phinity is an AI research lab focused on solving chip design. The bottleneck to AGI is compute, and we enable AI agents to tape-out chips autonomously, from architecture to post-silicon. We are building RL environments, agent infrastructure, and evaluation systems to accomplish this. Our team brings together deep AI and silicon expertise, including leaders and executives from top chip companies, post-training chip-design models at NVIDIA, AI for formal verification research, previous exits, and over 10 years of experience building chips at NVIDIA, Intel, Mediatek, and others.

We are hiring a Research Engineer to develop data in order to train and evaluate agents on hardware tasks.

You will

  • Build and scale out generation of novel, experimental environments for testing agents in real-world hardware engineering tasks
  • Profile and benchmark unreleased models
  • Run and experiment on research problems at the intersection of hardware engineering and reinforcement learning

What we’re looking for

  • Prior low-level systems and/or VLSI experience
  • Good research intuitions and rigorous engineering skills
  • Leadership skills; high ownership
  • ML/RL background is a plus
  • Operational experience is a plus

Why Phinity

  • Work directly with frontier AI labs to re-imagine ASIC design–see the frontier of intelligence before anyone else
  • Collaborate with our AI researchers and HW experts, with high leverage and ownership to develop new technologies

Benefits include

  • Health insurance
  • Retirement plans
  • Unlimited PTO
  • Paid parental leave
  • Lunch and dinner provided in-office

Source

Posted by Phinity Labs on their own hiring page, jobs.ashbyhq.com. OptiTalent shows it as published, read 07 Nov 2026 12:18 UTC; the original is the reference.

View the original ad ↗

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