Robot Learning Engineer

About the Role This is an entry-level research engineering role at an early-stage industrial robotics startup, sitting at the intersection of machine learning and real factory hardware. You'll apply state-of-the-art perception, reinforcement learning, and imitation learning to a physical robotic work cell built to automate demanding industrial tasks — surface finishing, welding, and coating. It's a rare opportunity for a hungry new grad to ship ML research directly onto production robots. What You'll Do Research and evaluate ML models for robot perception and task understanding. Apply computer vision and deep learning to multi-modal sensor data, including cameras, depth sensors, and force/torque inputs. Design and run experiments with reinforcement learning and imitation learning for robot control. Integrate trained AI models into a ROS 2–based robotics software stack. Iterate rapidly on experiments and translate research findings into real-world factory deployments. What We're Looking For BSc or MSc in Robotics, Computer Science, AI/ML, or a related field — or equivalent hands-on experience. 0–3 years of experience; strong fundamentals matter more than seniority. Proficiency in Python and experience with PyTorch or TensorFlow. Exposure to computer vision and/or robot learning (thesis, internship, open-source, or research counts). Familiarity with robotics simulation environments (e.g. Isaac Sim, MuJoCo, PyBullet) is a plus. Experience with sim-to-real transfer, 3D perception, or point clouds is a bonus. Research publications or coursework in RL or imitation learning are welcome signals. Eligible to work in Germany and able to work on-site in Munich — no visa sponsorship available. Location On-site in Munich, Bavaria, Germany . This role is fully on-site; remote work is not available. Candidates must already be eligible to work in Germany — visa sponsorship is not offered.