Entry-Level Robot Learning Engineer

Clera; München; Vor Ort; EUR 48.000 - 64.000; Vollzeit

Benefits dieser Stelle

Equity participation

Zusammenfassung

Clera invites a motivated entry-level researcher to join our small industrial robotics team in Munich. You will develop and evaluate perception, RL, imitation learning, and sim-to-real transfer for real-world robotic work cells, bridging research prototypes to deployment on factory hardware.

The role emphasizes Python proficiency, experience with PyTorch or TensorFlow, and familiarity with ROS/ROS 2. German language skills are a plus, and equity participation is available.

Qualifikationen

• Bachelor's or Master's in robotics, computer science, AI, machine learning or related field, or equivalent practical experience.
• 0–3 years of relevant experience in robot learning, robotics, computer vision, or ML for physical systems.
• Proficiency in Python and experience with PyTorch or TensorFlow.
• Exposure to computer vision or robot learning; familiarity with ROS/ROS2.
• Fluent English; German is a plus; familiarity with sim-to-real transfer, 3D perception, depth estimation, or point clouds is helpful.
• Research publications or open-source contributions are valued.

Aufgaben

• Research and evaluate machine learning models for robot perception and task understanding.
• Apply computer vision and deep learning to camera, depth, and sensor data.
• Experiment with reinforcement learning and imitation learning 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.

Kenntnisse

Python

English proficiency

Ausbildung

Bachelor's or Master's in Robotics/CS/AI/ML or related

Tools

PyTorch

TensorFlow

ROS/ROS2

Jobbeschreibung

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.