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
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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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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 software stack.
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Iterate rapidly on experiments and translate research findings into real-world factory deployments.
What We're Looking For
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BSc or MSc in Robotics, Computer Science, AI/ML, or a related field — or equivalent hands-on experience.
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0–3 years of experience; strong fundamentals matter more than seniority.
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Proficiency in Python and experience with PyTorch or TensorFlow.
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Exposure to computer vision and/or robot learning (thesis, internship, open-source, or research counts).
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Familiarity with robotics simulation environments (e.g. Isaac Sim, MuJoCo, PyBullet) is a plus.
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Experience with sim-to-real transfer, 3D perception, or point clouds is a bonus.
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Research publications or coursework in RL or imitation learning are welcome signals.
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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.