Senior AI / Reinforcement Learning Engineer (m/f/d)
Agile Robots SE is a high-tech startup based in Munich.
Agile Robots SE is a high-tech startup based in Munich.
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Warum dieser Job gelistet ist
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Agile Robots SE is a high-tech startup based in Munich. Our mission is to bridge the gap between AI and robotics by developing robotic systems that offer state-of-the-art full-body force sensitivity and world-leading vision intelligence. This unique combination of technologies enables us to provide intelligent, easy-to-use and affordable robotic solutions with safe human-robot interaction. We are a dynamic and innovative software development company dedicated to pushing the boundaries of technology. We specialize in creating cutting-edge solutions that transform industries and redefine user experiences. We are building humanoid robots that work reliably, autonomously, in the real world. As a Snr. AI/Reinforcement Learning Engineer, you will own the development of end-to-end control policies for Agile One: from training in simulation to deployment on hardware, across locomotion, manipulation, and whole-body coordination in unstructured environments. This is a high-ownership role. You will work at the frontier of what s possible with humanoid robots, make decisions with incomplete information, and iterate directly on physical systems. Success in this role requires both technical excellence and the ability to adapt and make decisions under uncertainty.
- Design, maintain and deploy scalable, end-to-end training pipelines, including hyperparameter optimization - Transfer control policies from simulation to real robotic hardware - Integrate learned policies into a full-stack robotic system, including perception, planning, and actuation - Analyze robot behavior and learning performance and iterate quickly based on real-world results - Evaluate and benchmark state-of-the-art algorithms - Stay updated with the latest research in RL and IL - Work autonomously on open-ended, evolving tasks Essential Skills - Master’s or PhD in robotics, computer science, engineering, or a related field - Proven experience (5+ years) applying RL or IL in physical systems, preferably on high DOF robots - Familiarity with common RL algorithms (PPO, SAC,.) - Proficiency in Python and/or C++, PyTorch, ONNX, and common RL frameworks (e.g, Stable Baselines 3, RSL-RL) - Experience with physics-based simulators (IsaacSim, MuJoCo or equivalent) for large-scale policy training - Strong understanding of control theory, motion planning, and robot kinematics/dynamics - Demonstrated success in sim-to-real transfer and deploying learning-based policies on physical robots - Strong problem-solving skills and the ability to work independently in uncertain scenarios Beneficial Skills - Experience in training locomotion and locomanipulation policies - Experience in training and deploying on humanoid robots - Track record of publishing at CoRL, ICRA, RSS, NeurIPS, or ICLR
- A dynamic high-tech company, combined with financial soundness and world-class investors. - Join an interdisciplinary, international team with 60+ different nationalities in a collaborative work environment. - Lots of development opportunities as we continue to grow. - Challenging tasks and impactful projects alongside experts that enable professional and personal growth. - Corporate
Agile Robots is a leading provider of AI-powered robotics solutions. By combining artificial intelligence and robotics, the company makes industries smarter, more flexible, and more efficient. Founded in Munich in 2018 by renowned robotics researchers from the German Aerospace Center (DLR), Agile Robots has experienced rapid global growth.
Today, more than 3,500 highly skilled robotics and AI enthusiasts are employed worldwide. The company has one of the largest research and development teams in the AI and robotics industry. Agile Robots has built a unique portfolio; together with the subsidiaries BÄR Automation, Franka Robotics, idealworks, and Krause Automation, the company covers all areas of AI-driven robotics.
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Zur OriginalanzeigeModelle bauen, trainieren und verbessern: von klassischem Machine Learning über Computer Vision bis zum Feinschliff großer Sprachmodelle.