Robot Learning Engineer, Human Motion Data (m/f/d)

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.