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Helping companies find solutions to supercharge growth

Machine Learning Engineer

Posted: 1 week ago
Job Location
Remote Work Policy

In office

Visa Sponsorship

Not Available

RelocationAllowed
Skills
Python
PyTorch
Jax

About the job

About the company

Our client is an early-stage robotics company building robots to help re-industrialize America, starting with electronics manufacturing. It designs its own hardware and trains its own models, is backed by top-tier venture firms, and plans to grow to about 20 people.

The role

Raydar is recruiting for this role on behalf of our client. You will own robot learning end to end, from data to deployed policy. The team just passed 100 hours of robot data and is scaling collection fast. This is applied work on real robots, not research for its own sake.

What you'll do

  • Build pipelines that ingest and quality-check terabytes of robot data a day
  • Post-train models and set up fast, reliable training pipelines
  • Calibrate hardware and run data QC so models perform well on the team's setup
  • Set the company's standards for data processing and model training
  • Track new robot learning research and apply what works

What we're looking for

  • 0 to 7 years of experience in robotics or machine learning
  • Hands-on experience with physical robots such as manipulators, drones or autonomous vehicles
  • Experience training and deploying learned policies on a real robot
  • Applied ML engineering background rather than purely academic research
  • Strong Python and working knowledge of PyTorch, JAX or similar
  • Open to working on defense-related projects

Tech stack: Python, PyTorch, JAX, C++, Rust

Bonus points

  • Experience at leading robotics or autonomous vehicle companies
  • Defense-tech experience
  • C++ or Rust proficiency
  • Distributed training or low-level GPU programming experience

Compensation and benefits

  • $150K-$250K base
  • 0.1% to 1% equity
  • Medical, dental and vision
  • Relocation available; visa sponsorship and transfers supported

Location and work model

  • San Francisco, CA (Potrero Hill)
  • On-site 5 days a week, plus Saturdays as needed
  • Full-time

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