About the Role
Join an industrial robotics team applying machine learning to real robotic work cells. You will help bring advances in perception and robot learning from research into practical manufacturing applications.
What You'll Do
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Research and evaluate machine learning models for robot perception and task understanding.
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Apply computer vision and deep learning to camera, force/torque, and depth sensor data.
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Experiment with reinforcement learning and imitation learning for robot control.
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Integrate AI models into a ROS 2 robotics stack.
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Run rigorous experiments, analyze results, and iterate on approaches.
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Connect research developments with real-world factory deployment.
What We're Looking For
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Approximately 0 to 3 years of relevant experience, including practical work through research, a thesis, an internship, or open-source contributions.
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A bachelor's or master's degree in robotics, computer science, AI/ML, or a related field, or equivalent practical experience.
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Proficiency in Python and experience with PyTorch or TensorFlow.
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Experience in computer vision or robot learning involving physical robotic systems.
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Fluent English; German is a plus.
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Familiarity with ROS or ROS 2 is helpful.
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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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Familiarity with 3D perception, point clouds, or depth estimation is beneficial.
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Research publications or open-source work in robotics or machine learning are valued.
Compensation & Benefits
Equity participation is available. Visa sponsorship is not available.
Location
On-site in Munich, Bavaria, Germany, five days per week.
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