Machine Learning Engineer
We're hiring a robotics machine learning engineer at a venture-backed robotics startup in San Francisco that builds its own hardware and trains its own models to automate electronics manufacturing. 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, and you'd own robot learning end to end, from data to deployed policy.
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 real robots
- Set the company's standards for data processing and model training
- Keep up with new robot learning research and apply what works
- What we're looking for0 to 7 years of applied machine learning engineering experience
- Hands-on work with physical robotic systems (robots, manipulators, drones or autonomous vehicles)
- You've trained and deployed a learned policy or ML model on real hardware
- Strong Python, plus PyTorch, JAX or an equivalent framework
Bonus: C++ or Rust, post-training policies, robot data collection
DetailsBase salary $150K to $250K plus 0.1% to 1% equity On-site 5 days a week in San Francisco (Potrero Hill), with occasional Saturdays. Relocation available Some of the work supports defense and government robotics applications Apply through the link on this post. It takes a few minutes and a recruiter will follow up quickly.