About the Role Join an industrial robotics team applying machine learning to real-world manufacturing tasks. This entry-level role combines research and hands-on experimentation to bring robot perception and learning methods into physical robotic systems. 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 experiments, analyze results, and iterate on approaches. • Help bridge research prototypes and deployment in industrial environments. What We're Looking For • Approximately 0 to 3 years of relevant experience, including research, internships, or practical projects. • A bachelor's or master's degree in robotics, computer science, AI/ML, or a related field, or equivalent practical experience. • Proficiency in Python and experience with PyTorch or TensorFlow. • Experience with computer vision or robot learning 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. • Exposure to 3D perception, point clouds, or depth estimation is beneficial. Research publications or open-source contributions in robotics or machine learning are also welcome. 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.