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.