About the Role
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.
What You'll Do
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Research and evaluate ML models for robot perception and task understanding.
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Apply computer vision and deep learning to multi-modal sensor data including cameras, force/torque sensors, and depth inputs.
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Design and run experiments with reinforcement learning and imitation learning for robot control.
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Integrate trained AI models into a ROS 2–based robotics stack.
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Iterate rapidly on experiments, maintaining rigorous evaluation standards.
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Bridge the gap between research and real-world factory deployment.
What We're Looking For
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0–3 years of experience; strong MSc or BSc in Robotics, Computer Science, AI, or a closely related field.
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Solid programming skills in Python, with hands-on experience in PyTorch or TensorFlow.
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Background in computer vision, robot learning, or physical autonomous systems — demonstrated through a thesis, internship, research, or open-source work.
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Familiarity with ROS 2 or a strong motivation to learn it quickly.
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Experience with sim-to-real transfer or simulators such as Isaac Sim, PyBullet, or MuJoCo is a plus.
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Exposure to 3D perception, point clouds, or depth estimation is a plus.
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Research publications or reproducible project work are a bonus signal.
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Must be eligible to work in Germany and able to work on-site in Munich — no visa sponsorship is available.
Compensation & Benefits
Equity participation is included. Cash compensation details will be confirmed during the interview process. No visa sponsorship is available.
Location
On-site in Munich, Bavaria, Germany. This role is not available remotely.