Robot Learning Engineer
About Mkind
mkind is an early-stage robotics startup on a mission to automate the hardest, most painful manual industrial tasks. We build fully flexible, intelligent robotic work cells for surface finishing, welding, and coating. We are a small, focused team moving fast and building things that matter in the physical world.
About the Role
We are looking for a Robot Learning Research Scientist to join us at an early and formative stage. You will be a core member of our technical team, driving the research that enables our robots to perceive, understand, and autonomously perform complex industrial tasks such as surface finishing, welding, and coating. This is a rare opportunity to work across the full stack of robot learning, from developing and testing algorithms in simulation to deploying them on real hardware in industrial environments. You will collaborate directly with the founders, shape our research agenda, and have a tangible impact on how automation evolves in manufacturing.
What You'll Do
Research, develop, and evaluate AI and ML models for robot perception and task understanding
Develop and experiment with reinforcement learning and imitation learning approaches for robot control
Run experiments, analyze results, and iterate quickly on hypotheses
Collaborate closely with the founders to bridge research and real-world deployment
Stay up to date with relevant research and bring new ideas to the team
What We're Looking For
MSc or PhD (or equivalent industrial research experience) and publications in Robot Learning, with contributions to venues like CoRL, ICRA, IROS, RSS, ICLR, ICML, NeurIPS, or similar
Strong knowledge and experience of applying reinforcement learning, imitation learning, and robot vision algorithms to simulation and/or real robot platforms
Familiarity with generative modeling (Diffusion models, Flow matching) and modern foundation model architectures (VLMs, VLAs, World models)
Strong proficiency in Python and modern machine learning frameworks (PyTorch, TensorFlow)
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
Nice to Have
Familiarity with 3D perception, point clouds, or depth estimation
Experience with sim-to-real transfer or physics-based simulation (e.g. Isaac Sim, PyBullet, MuJoCo)
Experience with Agentic AI systems (e.g., LLM-based agents, tool use, RAG systems, multi-step reasoning), with an interest in applying them to robotic systems
Experience with ROS/ROS2 and Docker
Experience in industrial automation and manufacturing processes
Compensation & Location
Location: Munich, Germany (on-site)
Equity participation as an early team member
Join us in building the hardware and software foundation stack that will foster the next generation of automation in industrial manufacturing.