(Senior) AI / Reinforcement Learning Engineer (m/f/d)

About This Opportunity

Our talent team is representing a confidential robotics organization based in Munich, Bavaria. We are seeking a Senior AI / Reinforcement Learning Engineer to take ownership of end-to-end control policy development for advanced robotic systems—from simulation training through hardware deployment.

This is a high-ownership role working at the frontier of intelligent robotics. You will make critical decisions with incomplete information, iterate directly on physical systems, and deploy learning-based policies across locomotion, manipulation, and whole-body coordination in unstructured real-world environments.

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 full-stack robotic systems including perception, planning, and actuation
• Analyze robot behavior and learning performance, iterating quickly based on real-world results
• Evaluate and benchmark state-of-the-art algorithms in reinforcement learning and imitation learning
• Stay current with the latest research in RL and IL
• Work autonomously on open-ended, evolving tasks

What We're Looking For

Essential Requirements:

• Master's or PhD in robotics, computer science, engineering, or related field
• 5+ years of proven experience applying RL or IL in physical systems, preferably on high-DOF robots
• Familiarity with common RL algorithms (PPO, SAC, etc.)
• 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 ability to work independently in uncertain scenarios

Beneficial Experience:

• Training locomotion and locomanipulation policies
• Training and deploying on humanoid robots
• Track record of publishing at CoRL, ICRA, RSS, NeurIPS, or ICLR

How We Work With You

Candidates apply directly through Get A Job.ai. Our recruiting team will screen qualified applicants and coordinate submissions to our client. We manage the entire interview process and provide guidance at each stage. Please do not contact the client organization directly—all communication flows through our team to ensure a professional, coordinated experience.

Location and Benefits

This position is based in Munich, Bavaria, Germany. Our client offers corporate benefits covering health, mobility, and learning, modern office facilities, and opportunities for professional growth within an international team environment.

Equal Opportunity: Get A Job.ai is committed to inclusive recruiting practices. We welcome applications regardless of gender, sexual identity, nationality, ethnicity, religion, age, or disability status.