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# Robot Learning Engineer

- **Company:** Clera
- **Location:** München, Germany
- **Experience:** Starter
- **Contract:** Internship / Graduate position
- **Skills:** Artificial Intelligence, Computer Vision, Python (Programming Language), Machine Learning, Tensorflow, Reinforcement Learning, Pytorch, Deep Learning, Information Technology
- **Published:** May 26, 2026
- **Apply:** https://de.indeed.com/viewjob?jk=4d6a7772f11aa278

## About the Role

Do you have a Master's degree?, * Bachelor's or Master's degree in Robotics, Computer Science, AI, or a related field

 * 0-3 years of hands-on experience in robotics, computer vision, or AI research
 * Proficiency in Python and at least one deep learning framework (PyTorch or TensorFlow)
 * Experience with ROS 2
 * Experience with computer vision and sensor data processing for robotics
 * Experience with reinforcement learning and/or imitation learning for robot control

Nice to Have:

 * Experience with sim-to-real tools such as Isaac Sim, MuJoCo, or PyBullet
 * Research publications, a strong thesis, internships, or open-source contributions in robotics or AI
 * Background in 3D perception, point clouds, or depth estimation

## Description

Join a small, ambitious early-stage industrial robotics startup in Munich at the frontier of robot learning. This is an entry-level research role where you'll apply state-of-the-art machine learning - perception, reinforcement learning, imitation learning, and sim-to-real transfer - to a real industrial robotic work cell tackling hard manual tasks like surface finishing, welding, and coating. You'll have the rare opportunity to ship ML research directly onto physical factory hardware from day one., * 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 the ROS 2 robotics stack
 * Run rigorous experiments and iterate quickly in a fast-paced research environment
 * Bridge the gap between research and real-world factory deployment


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