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
Research and evaluate machine learning models for robot perception and task understanding.
Apply computer vision and deep learning to camera, depth, and force or torque sensor data.
Experiment with reinforcement learning and imitation learning approaches for robot control.
Integrate AI models into a ROS 2 robotics stack.
Run rigorous experiments, analyze results, and iterate on models and system performance.
Help bridge research prototypes and deployment on real factory hardware.
What We're Looking For
Approximately 0 to 3 years of relevant experience, with a background in robot learning, robotics, computer vision, or machine learning for physical systems.
A bachelor's or master's degree in robotics, computer science, AI, machine learning, or a related field, or equivalent practical experience.
Proficiency in Python and experience with a deep-learning framework such as PyTorch or TensorFlow.
Exposure to computer vision or robot learning, and familiarity with ROS or ROS 2.
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.