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Entry-Level Robot Learning Engineer

On-site
CleraMunich, DE1 day agoWebsite
Fresh
Full-time
Entry / Junior
Engineering

Compensation

Salary undisclosed
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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.

Stack

Computer VisionPythonPyTorchMachine LearningDeep LearningReinforcement LearningRoboticsTensorFlow
Posted
Oct 3, 2026
Last seen
Oct 3, 2026
First seen
Oct 3, 2026

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