ABOUT THE ROLE Join a team building intelligent robotic systems for demanding industrial applications. In this entry-level role, you will apply machine learning to physical robots, helping translate research in perception and robot learning into practical factory deployment. WHAT YOU'LL DO - Research and evaluate machine learning models for robot perception and task understanding. - Apply computer vision and deep learning to camera, force and torque, and depth sensor data. - Experiment with reinforcement learning and imitation learning for robot control. - Integrate AI models into a ROS 2 robotics stack. - Run rigorous experiments and iterate on approaches using physical robotic systems. - Connect research results to real-world industrial deployment.
WHAT WE'RE LOOKING FOR - Approximately 0 to 3 years of relevant experience, including research, internships, or practical projects. - A BSc or MSc in robotics, computer science, AI/ML, or a related field, or equivalent practical experience. - Proficiency in Python and experience with PyTorch or TensorFlow. - Computer vision or robot-learning experience involving physical robotic systems. - Fluent English; German is a plus. - Familiarity with ROS or ROS 2, physics simulation tools such as Isaac Sim, PyBullet, or MuJoCo, and sim-to-real transfer is beneficial. - Experience with 3D perception, point clouds, or depth estimation is beneficial, as are robotics or machine learning publications and open-source contributions.
COMPENSATION & BENEFITS Equity participation is available. Visa sponsorship is not available. LOCATION On-site, five days per week in Munich, Bavaria, Germany. Candidates must be eligible to work in Germany.
Job description provided by Clera.
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