Robot Learning Engineer

About the Role This is an entry-level research and engineering role at an early-stage industrial robotics startup, where you will apply state-of-the-art machine learning directly to a real robotic work cell automating demanding factory tasks such as surface finishing, welding, and coating. You will work within a small, ambitious team at the intersection of AI research and physical deployment, shipping models onto real hardware in a production environment. What You'll Do Research and evaluate ML models for robot perception and task understanding. Apply computer vision and deep learning to sensor data including cameras, force/torque sensors, and depth sensors. Experiment with reinforcement learning and imitation learning for robot control. Integrate AI models into a ROS 2 robotics software stack. Run rigorous experiments, measure results carefully, and iterate quickly. Bridge the gap between research prototypes and real-world factory deployment. What We're Looking For 0 to 3 years of experience, including new graduates welcome. BSc or MSc in Robotics, Computer Science, AI/ML, or a closely related field, or equivalent practical experience. Background directly relevant to robot learning, such as robotics, computer vision, or ML for physical systems. Strong proficiency in Python and hands-on experience with PyTorch or TensorFlow. Enthusiasm for working with physical systems and deploying AI on real robots. Rigorous experimental mindset with a bias for fast iteration. Fluent English; German is a plus. Familiarity with ROS or ROS 2 is a bonus. Experience with sim-to-real transfer or physics simulators such as Isaac Sim, PyBullet, or MuJoCo is a bonus. Familiarity with 3D perception, point clouds, or depth estimation is a bonus. Research publications or open-source contributions in robotics or ML are a bonus. Compensation & Benefits Equity participation is included. Cash compensation details are available on request. Visa sponsorship is not available; candidates must already be eligible to work in Germany. Location On-site in Munich, Bavaria, Germany, five days per week.