Act as hands-on trainer for NeuraGym users: design training curricula, scope task feasibility, and plan demonstration/data-collection sessions for robot skill acquisition
Onboard users to the full NeuraGym pipeline: teleoperation, annotation, training, simulation, deployment, and validation
Collaborate closely with robotics engineers during data capture and live demonstrations to ensure desired behaviors and safety standards are achieved
Guide users through model training and refinement: review training scripts, identify data quality issues, help reproduce and resolve learning failures; step in hands-on when a blocker persists
Serve as a key interface between trainees/users and the cloud and AI teams, facilitating collaboration and support where needed
Feed lessons learned from training sessions back into both the NeuraGym product roadmap and the Neura core AI roadmap
Master's degree in Computer Science, Robotics, Electrical Engineering, or related field
3+ years of hands-on experience in robot learning or physical AI training
Solid Python skills (C++ a plus); practical experience with PyTorch or TensorFlow
Comfortable working directly with real robot hardware, teleoperation setups, and associated middleware
Cloud experience (AWS, Azure, or GCP) and experience with robotic simulation tools (IsaacSim, MuJoCo, etc.) is a plus
Strong instructional and problem-solving abilities; able to manage multiple training projects in parallel
Clear communicator who can translate between researchers, engineers, and end-users, with good command of English and German (B2–C1 level)
