This is an entry-level research and engineering role at a small, ambitious industrial robotics startup in Munich. You will apply state-of-the-art machine learning directly to a real robotic work cell, tackling some of the hardest automation challenges in manufacturing, including surface finishing, welding, and coating. It is a rare opportunity for a hungry new graduate to ship AI on real factory 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, depth sensors, and force/torque inputs.
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Experiment with reinforcement learning and imitation learning for robot control.
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Integrate trained AI models into a ROS 2 robotics stack.
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Run rigorous experiments, measure results carefully, and iterate quickly.
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Bridge the gap between research prototypes and real-world factory deployment.
What We’re Looking For
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0 to 3 years of experience, including new graduates with strong fundamentals.
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BSc or MSc in Robotics, Computer Science, AI/ML, or a related field, or equivalent practical experience.
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Background directly relevant to robot learning, such as robotics, computer vision, or ML for physical systems.
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Strong proficiency in Python with hands-on experience in PyTorch or TensorFlow.
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Exposure to computer vision or robot learning, whether through coursework, a thesis, an internship, or open-source work.
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Rigorous experimental mindset and genuine enthusiasm for deploying AI on physical systems.
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Fluent English; German is a bonus.
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Familiarity with ROS or ROS 2 is a plus.
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Experience with sim-to-real transfer or physics simulators such as Isaac Sim, PyBullet, or MuJoCo is a plus.
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Knowledge of 3D perception, point clouds, or depth estimation is a plus.
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Research publications or open-source contributions in robotics or ML are a plus.
Compensation & Benefits
Equity participation is included. Visa sponsorship is not available; candidates must already be eligible to work in Germany.
Location
On-site, five days per week in Munich, Bavaria, Germany. Remote work is not available for this role.