Robotics Data Engineer, Human Motion Data (m/f/d)

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.

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 build pipelines that turn raw exoskeleton recordings into clean, robot-ready training data, including retargeting human motion to the humanoid’s body. So in the future human workers and robots can work side by side on the same tasks.

Define signals, formats and metadata for our next exoskeleton generation

Build pipelines from devices in the field to storage, incl. sync, calibration and versioning

Build tooling for quality checks, segmentation, annotation and dataset export

Implement anonymization, consent handling and GDPR-compliant data flows

Set up storage and compute together with our robot learning team

Degree in CS, data engineering, robotics or similar, with hands-on pipeline experience

Strong Python and SQL; pipeline tools (e.g. Airflow, Ray or Spark)

Time-series or multimodal sensor data, incl. synchronization and calibration

Cloud (AWS, GCP or Azure), Docker and Linux

Solid un