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This is an entry-level research engineering role at an early-stage industrial robotics startup, where you'll apply state-of-the-art machine learning directly to a real robotic work cell on the factory floor. You'll sit at the intersection of ML research and physical deployment, helping automate some of the most demanding manual tasks in industry — including surface finishing, welding, and coating. It's an excellent opportunity for a hungry new grad who wants to ship AI on real hardware from day one.
Research and evaluate ML models for robot perception and task understanding.
Apply computer vision and deep learning to multi-modal sensor data including cameras, force/torque sensors, and depth inputs.
Design and run experiments with reinforcement learning and imitation learning for robot control.
Integrate trained AI models into a ROS 2–based robotics stack.
Iterate rapidly on experiments, maintaining rigorous evaluation standards.
Bridge the gap between research and real-world factory deployment.
0–3 years of experience; strong MSc or BSc in Robotics, Computer Science, AI, or a closely related field.
Solid programming skills in Python, with hands-on experience in PyTorch or TensorFlow.
Background in computer vision, robot learning, or physical autonomous systems — demonstrated through a thesis, internship, research, or open-source work.
Familiarity with ROS 2 or a strong motivation to learn it quickly.
Experience with sim-to-real transfer or simulators such as Isaac Sim, PyBullet, or MuJoCo is a plus.
Exposure to 3D perception, point clouds, or depth estimation is a plus.
Research publications or reproducible project work are a bonus signal.
Must be eligible to work in Germany and able to work on-site in Munich — no visa sponsorship is available.
Equity participation is included. Cash compensation details will be confirmed during the interview process. No visa sponsorship is available.
On-site in Munich, Bavaria, Germany. This role is not available remotely.
