About the Role
Join a small industrial robotics team applying machine learning to real-world robotic work cells. In this entry-level research role, you will develop and evaluate approaches in perception, reinforcement learning, imitation learning, and sim-to-real transfer, helping bring intelligent automation to challenging industrial tasks.
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, depth, and force or torque sensor data.
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Experiment with reinforcement learning and imitation learning approaches 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 models and system performance.
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Help bridge research prototypes and deployment on real factory hardware.
What We're Looking For
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Approximately 0 to 3 years of relevant experience, with a background in robot learning, robotics, computer vision, or machine learning for physical systems.
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A bachelor's or master's degree in robotics, computer science, AI, machine learning, or a related field, or equivalent practical experience.
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Proficiency in Python and experience with a deep-learning framework such as PyTorch or TensorFlow.
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Exposure to computer vision or robot learning, and familiarity with ROS or ROS 2.
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Fluent English; German is a plus. Familiarity with simulation tools, sim-to-real transfer, 3D perception, point clouds, or depth estimation is helpful. Research publications or open-source contributions are also valued.
Compensation & Benefits
Equity participation is available. Visa sponsorship is not available, and candidates must be eligible to work in Germany.
Location
On-site, five days per week in Munich, Bavaria, Germany.
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