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.
- Locations
- München, Bavaria, Germany
- Education
- bachelor degree and postgraduate degree