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.