Robot Learning Engineer
About the Role
This is an entry-level research and engineering role at a small, ambitious industrial robotics startup in Munich. You will apply state-of-the-art machine learning directly to a real robotic work cell, tackling some of the hardest automation challenges in manufacturing, including surface finishing, welding, and coating. It is a rare opportunity for a hungry new graduate to ship AI on real factory hardware from day one.
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.
Experiment with reinforcement learning and imitation learning for robot control.
Integrate trained AI models into a ROS 2 robotics 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 with strong fundamentals.
BSc or MSc in Robotics, Computer Science, AI/ML, or a 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 with hands-on experience in PyTorch or TensorFlow.
Exposure to computer vision or robot learning, whether through coursework, a thesis, an internship, or open-source work.
Rigorous experimental mindset and genuine enthusiasm for deploying AI on physical systems.
Fluent English; German is a bonus.
Familiarity with ROS or ROS 2 is a plus.
Experience with sim-to-real transfer or physics simulators such as Isaac Sim, PyBullet, or MuJoCo is a plus.
Knowledge of 3D perception, point clouds, or depth estimation is a plus.
Research publications or open-source contributions in robotics or ML are a plus.
Compensation & Benefits
Equity participation is included. Visa sponsorship is not available; candidates must already be eligible to work in Germany.
Location
On-site, five days per week in Munich, Bavaria, Germany. Remote work is not available for this role.