Robot Learning Engineer, Human Motion Data (m/f/d)
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职位描述
About EASE EASE builds active, AI-powered exoskeletons for logistics and manufacturing. As a TUM spin-off, we have just started series production, and paid pilots with well-known logistics companies have led to first purchase orders. Our goal: move every parcel better, manually with an exoskeleton or autonomously with a robot.
The role Our exoskeletons are deployed in real warehouses and production plants and capture what video-only datasets miss: body pose, joint kinematics, interaction torques, vision, and hand forces from real human work. Your job is to turn that data into skills our humanoid can actually perform, so that human workers and robots can work side by side on the same tasks.
What you'll do Map human motion onto humanoid kinematics and close the embodiment gap
Train manipulation and whole-body policies with imitation and reinforcement learning
Evaluate in Isaac Lab or MuJoCo and on our in-house humanoid, and measure the value of our data
Define what data training needs and help build our training setup, including GPU compute
Turn new research on robot foundation models and VLAs into prototypes
What you bring Master's or PhD in robotics, CS, ML or similar, with hands-on experience from industry or research
Imitation or reinforcement learning on real robots (e.g. Diffusion Policy, ACT, PPO)
Strong Python and PyTorch; C++ is a plus
Physics simulation and sim-to-real transfer
Solid kinematics, dynamics and control
Nice to have Learning from human data (egocentric video, motion capture, retargeting)
Humanoids, legged robots or exoskeletons; publications at CoRL, RSS, ICRA or NeurIPS
Don't tick every box? Apply anyway. What you have built matters more than a perfect match.
What we offer Data almost nobody else has, from a product in series deployment
Our own humanoid and the chance to build Physical AI at EASE from the ground up
Competitive salary plus virtual stock options (VSOP)
Flexible hours, hybrid in Munich, mobility benefit
Budget for conferences and further training
How to apply Send your CV with links to GitHub, papers or robot videos.
Martin Fleischer, CEO & Co-Founder
EASE is an equal opportunity employer. Applicants need a valid work permit for the EU.
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