You’ll apply on Clera’s own site.
About the Role
Join a team building intelligent robotic systems for demanding industrial applications. In this entry-level role, you will apply machine learning to physical robots, helping translate research in perception and robot learning into practical factory deployment.
What You’ll Do
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Research and evaluate machine learning models for robot perception and task understanding.
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Apply computer vision and deep learning to camera, force and torque, and depth sensor data.
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Experiment with reinforcement learning and imitation learning for robot control.
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Integrate AI models into a ROS 2 robotics stack.
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Run rigorous experiments and iterate on approaches using physical robotic systems.
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Connect research results to real-world industrial deployment.
What We’re Looking For
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Approximately 0 to 3 years of relevant experience, including research, internships, or practical projects.
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A BSc or MSc in robotics, computer science, AI/ML, or a related field, or equivalent practical experience.
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Proficiency in Python and experience with PyTorch or TensorFlow.
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Computer vision or robot-learning experience involving physical robotic systems.
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Fluent English; German is a plus.
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Familiarity with ROS or ROS 2, physics simulation tools such as Isaac Sim, PyBullet, or MuJoCo, and sim-to-real transfer is beneficial.
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Experience with 3D perception, point clouds, or depth estimation is beneficial, as are robotics or machine learning publications and open-source contributions.
Compensation & Benefits
Equity participation is available. Visa sponsorship is not available.
Location
On-site, five days per week in Munich, Bavaria, Germany. Candidates must be eligible to work in Germany.