(Senior) AI / Reinforcement Learning Engineer (m/f/d) Munich, Bavaria, Germany

Agile Robots SE; München; Hybrid; EUR 90.000 - 120.000; Vollzeit

Benefits dieser Stelle

Corporate Benefits Program

Munich office with rooftop access

Regular company events

Zusammenfassung

Agile Robots SE in Munich is seeking a Reinforcement Learning Engineer to own end-to-end control policy development—from simulation training to deployment on humanoid robots in real-world environments.

The role requires 5+ years in RL/IL for physical systems, strong Python/C++ skills, and experience with RL frameworks and physics-based simulators. You will operate in a high-ownership setting and influence hardware-software integration.

Qualifikationen

• Master’s or PhD in robotics, CS, engineering, or related field.
• 5+ years applying RL/IL to physical systems.
• Experience with sim-to-real transfer.
• Proficiency in Python and/or C++.
• Familiarity with RL algorithms (PPO, SAC).
• Experience with physics-based simulators (IsaacSim, MuJoCo).

Aufgaben

• 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.
• Demonstrated success in sim-to-real transfer and deploying learning-based policies on physical robots.

Kenntnisse

RL/IL expertise

Python/C++

RL algorithms (PPO, SAC)

Control theory

Motion planning

Robot kinematics/dynamics

Sim-to-real transfer

Ausbildung

Master/PhD in robotics or CS/engineering

Tools

PyTorch

ONNX

Stable Baselines 3

RSL-RL

IsaacSim

MuJoCo

Jobbeschreibung

About the role

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.

Your Responsibilities

• 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, e 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


• 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

What we offer

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 Benefits Program covering health, mobility, and learning for 100€ net per month.

Modern office facilities with a rooftop terrace overlooking Munich, free drinks & fruit, and regular company events contribute to a good working environment

About us

Agile Robots SE is an international high-tech company based in Munich, Germany with a production site in Kaufbeuren and more than 3500 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.