This is an entry-level research and engineering role at an early-stage industrial robotics startup, where you will apply state-of-the-art machine learning directly to a real robotic work cell automating demanding factory tasks such as surface finishing, welding, and coating. You will work within a small, ambitious team at the intersection of AI research and physical deployment, shipping models onto real hardware in a production environment.
Research and evaluate ML models for robot perception and task understanding.
Apply computer vision and deep learning to sensor data including cameras, force/torque sensors, and depth sensors.
Experiment with reinforcement learning and imitation learning for robot control.
Integrate AI models into a ROS 2 robotics software stack.
Run rigorous experiments, measure results carefully, and iterate quickly.
Bridge the gap between research prototypes and real-world factory deployment.
0 to 3 years of experience, including new graduates welcome.
BSc or MSc in Robotics, Computer Science, AI/ML, or a closely related field, or equivalent practical experience.
Background directly relevant to robot learning, such as robotics, computer vision, or ML for physical systems.
Strong proficiency in Python and hands-on experience with PyTorch or TensorFlow.
Enthusiasm for working with physical systems and deploying AI on real robots.
Rigorous experimental mindset with a bias for fast iteration.
Fluent English; German is a plus.
Familiarity with ROS or ROS 2 is a bonus.
Experience with sim-to-real transfer or physics simulators such as Isaac Sim, PyBullet, or MuJoCo is a bonus.
Familiarity with 3D perception, point clouds, or depth estimation is a bonus.
Research publications or open-source contributions in robotics or ML are a bonus.
Equity participation is included. Cash compensation details are available on request. Visa sponsorship is not available; candidates must already be eligible to work in Germany.
On-site in Munich, Bavaria, Germany, five days per week.
Job details are sourced from the employer's original posting.
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