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 physical robotic work cell built for demanding manufacturing tasks like surface finishing, welding, and coating. You will sit on a small, ambitious team in Munich and own the full loop from research to real-world factory deployment.
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 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 findings and practical deployment on factory hardware.
What We're Looking For
BSc or MSc in Robotics, Computer Science, AI/ML, or a closely related field, or equivalent hands-on experience.
0 to 3 years of experience, including new graduates with strong fundamentals and relevant project or thesis work.
Proficiency in Python and experience with PyTorch or TensorFlow.
Background touching robot learning, computer vision, or ML for physical systems; a pure NLP or LLM focus is not a strong fit.
Genuine enthusiasm for working with physical systems and deploying AI on real robots.
Eligible to work in Germany and able to commit to full-time, on-site work in Munich.
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.
Exposure to 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. Visa sponsorship is not available for this role.
Location
On-site, five days per week in Munich, Bavaria, Germany.