Robot Learning Engineer, Human Motion Data

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

• 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, EASE is an equal opportunity employer. Applicants need a valid work permit for the EU.

• 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

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., EASE

Gardening and landscaping