Your Mission
Build and ship learning-based control systems that power humanoid robots in the real world
Train and deploy policies using reinforcement learning, imitation learning, and multimodal foundation-model approaches with embodied perception
Hack on simulation and real-world setups to close the sim-to-real gap and move faster from experiment to deployment
Dig into the full robotics stack to chase down latency, bottlenecks, and weird failure modes
Create intuitive teleoperation and human-in-the-loop tools to accelerate data collection and evaluation
Work side-by-side with a small team of engineers and scientists who care about moving fast and building things that last
What You Bring to the Table
A strong drive to get humanoid robots working in the messy real world—not just in papers or demos
Ability to take full ownership: spotting problems, proposing solutions, and pushing them through to deployment
Solid experience with machine learning for robotics (RL, IL, VLA, or related), plus comfort jumping between code, data, and hardware
Production-level Python or C++ skills
3/5+ years of hands-on contributions in robotics, ML, or similar—whether from industry projects, research labs, or your own builds
Care for detail: clean code, reliable experiments, and datasets that don’t crumble under pressure
Bonus: you’ve tinkered with humanoids before
We value exceptional builders over perfect resumes. If you don’t meet every criterion but believe you can have an outsized impact, we strongly encourage you to apply
Skills Required
- Solid experience with machine learning for robotics
- Production-level Python skills
- Production-level C++ skills
- 3/5+ years of hands-on contributions in robotics or ML
- Bonus: experience with humanoid robots
What We Do
We build general-purpose mobile and humanoid robots capable of human-level dexterity and understanding of the physical world. It will enable people to focus on what truly matters in their lives. We are based in Paris, FR. Join us: https://app.dover.com/jobs/uma
