Robot Learning Engineer

About the RoleThis 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 DoResearch 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 ForBSc 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.LocationOn-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.