Robot Learning Engineer

Mkind is an early-stage robotics startup on a mission to automate the most critical and demanding jobs in industry. We are building a fully flexible, intelligent robotic work cell designed specifically for the hardest manual industrial tasks — surface finishing, welding, and coating. Small, ambitious team in Munich at the frontier of industrial robotics.

Join us at an early and formative stage. You'll work on developing the AI and machine learning capabilities that make our robotic work cell truly intelligent — enabling it to perceive its environment, reason about tasks, and adapt to the complex and variable conditions of real industrial processes.

This is an entry-level research role with broad scope. You will work hands-on with real robot hardware and real industrial use cases from day one, applying state-of-the-art AI techniques to problems that genuinely matter.

• Research, develop, and evaluate AI / ML models for robot perception and task understanding.
• Apply computer vision and deep learning to process sensor data (cameras, force/torque, depth).
• Develop and experiment with reinforcement learning and imitation learning approaches for robot control.
• Integrate AI models into the broader robotics software stack (ROS 2).
• Run experiments, analyze results, and iterate quickly on hypotheses.
• Collaborate closely with robotics engineers to bridge research and real-world deployment.
• Stay up to date with relevant research and bring new ideas to the team.

• MSc or BSc in Robotics, Computer Science, AI / ML, or a related field (or equivalent practical experience).
• Solid understanding of machine-learning fundamentals and deep-learning frameworks (PyTorch or TensorFlow).
• Experience with computer vision and/or robot learning (academic projects, thesis, or internships are welcome).
• Proficiency in Python; familiarity with ROS / ROS 2 is a plus.
• Strong analytical mindset and a habit of rigorous experimentation.
• Enthusiasm for working on physical systems and seeing AI deployed in the real world.
• Fluent in English; German is a plus.

• Experience with sim-to-real transfer or physics-based simulation (e.g. Isaac Sim, PyBullet, MuJoCo).
• Familiarity with 3D perception, point clouds, or depth estimation.
• Research publications or open-source contributions in robotics or ML.
• Interest in industrial automation and manufacturing processes.

Location: Munich, Germany (on-site, 5 days/week)
Equity participation as an early team member.