Robot Learning Engineer
About the Role
This is an entry-level research and engineering position at a small, ambitious industrial robotics startup in Munich. You'll apply state-of-the-art machine learning - spanning perception, reinforcement learning, and imitation learning - directly to a real robotic work cell built to automate some of the most demanding manual tasks in industry: surface finishing, welding, and coating. Expect tight research-to-hardware feedback loops and the satisfaction of seeing your models run on physical factory equipment.
What You'll Do
Research, evaluate, and prototype ML models for robot perception and task understanding
Apply computer vision and deep learning to multi-modal sensor data (RGB cameras, depth sensors, force/torque)
Design and run experiments with reinforcement learning and imitation learning for robot control
Integrate trained AI models into a ROS 2-based robotics stack
Iterate rapidly on experiments and maintain rigorous evaluation practices
Bridge the gap between research prototypes and real-world factory deployment
What We're Looking For
Required
BSc or MSc in Robotics, Computer Science, AI, or a closely related field
Strong Python skills and hands-on experience with PyTorch or TensorFlow
Practical exposure to computer vision and/or robot learning (thesis, internship, open-source, or research project)
Genuine interest in physical systems and real-world robotics - not purely software or NLP backgrounds
0-3 years of professional or research experience
Eligible to work in Germany and able to work on-site in Munich (no visa sponsorship available)
Nice to Have
Experience with robot simulation environments: Isaac Sim, MuJoCo, or PyBullet
Sim-to-real transfer techniques
3D perception: point clouds, depth estimation, or 3D scene understanding
Familiarity with ROS 2
Research publications or competition results in robotics / ML
Compensation & Benefits
Equity participation - meaningful stake in an early-stage company
Cash compensation details to be discussed directly during the interview process
Small team environment with high ownership and direct impact
Location
This role is fully on-site in Munich, Germany. Candidates must already be eligible to work in Germany; visa sponsorship is not available. Candidates willing to relocate to Munich are welcome to apply.
