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 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.
Agile Robots SE is an international high-tech company based in Munich, Germany with a production site in Kaufbeuren and more than 2300 employees worldwide. Our mission is to bridge the gap between artificial intelligence and robotics by developing systems that combine state-of-the-art force-moment-sensing and world-leading image-processing technology. This unique combination of technologies allows us to provide user-friendly and affordable robotic solutions that enable intelligent precision assembly.
This is made possible by our employees, who bring out the best in each and every day with creativity and enthusiasm. Become part of this team and shape the future of robotics with us!
We are proud of our diversity and welcome your application regardless of gender and sexual identity, nationality, ethnicity, religion, age, or disability.
#J-18808-LjbffrVeröffentlichungsdatum:
31 Jul 2026Standort:
MünchenEinsatzort:
Gemmingen, GermanyTyp:
VollzeitArbeitsmodell:
Vor OrtKategorie:
Erfahrung:
2+ yearsArbeitsverhältnis:
Angestellt
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