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.