Machine Learning Engineer
Jack
San Francisco, CA0–7 yrs2h agovia LinkedIn
This job at a glance
- Who can apply
- New grads and up to 7 years
- Must know
- Machine learningNetworking
- Nice to have
- PythonPyTorchC++Rust
- Work
- On-site in San Francisco
- Pay
- Not stated by the employer.
- Skill demand
- Python84%Machine learning74%PyTorch38%Networking4%of 99 similar entry-level jobs posted in the US this week
- Listed
- Nov 3, 2026 · still open
Sign in free to see which of these skills your resume already shows.
About the Role
We're hiring a 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. 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. The team just passed 100 hours of robot data and is scaling collection fast.
Key Responsibilities
- 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.
Requirements & Tech Stack
- 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.
Qualifications
- 0 to 7 years of applied machine learning engineering experience.