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

About […]

[…] 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.

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.

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

Learning from human data (ego