Entry-Level Robot Learning Engineer
Clera · Munich
Open. First seen 3 October 2026.
Description
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.
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