Founding Robot Learning Engineer
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You'll teach robots new skills in the field, and make them more capable with every deployment.
What you'll own
- The manipulation stack: collecting teleoperation data, then training, evaluating and deploying policies (imitation learning, fine-tuned VLA/foundation models)
- The path to autonomy task by task: teleoperation, then assisted autonomy, then supervised end-to-end autonomy
- Reinforcement learning post-training in simulation, sim-to-real transfer, and distilling models to run on the robot's onboard computer
- The data flywheel that turns every field deployment into better models across tasks and markets
Profile
- Has trained and deployed imitation-learning or RL policies on real robots, in the field
- Has shipped models that run in real time within an edge compute budget
- Strong in PyTorch, data pipelines and robot evaluation, reads papers and builds from them
- Background from a robot learning lab or industry team (manipulation, humanoids, mobile manipulation)
What we look for
Real work over credentials. Show us what you have built: projects, a portfolio, open source, what you shipped in past roles. That's what we look at first.
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