AI Software Engineer, Reinforcement Learning (f/m/d)

About This Opportunity

We are representing a confidential robotics client developing advanced manipulation systems for industrial deployment. This is a product-focused role with real hardware, real customers, and real impact—not a pure research position.

As an AI Software Engineer specializing in Reinforcement Learning, you will build the learning systems that enable dexterous robotic manipulation through experience and interaction. You'll work across simulation, policy development, and hardware integration to create scalable, adaptive robotic skills that perform reliably in production environments.

Responsibilities

• Develop reinforcement learning algorithms for complex manipulation tasks
• Design training environments, reward functions, and learning curricula
• Train and evaluate policies in simulation and validate on physical hardware
• Implement methods for efficient exploration, learning, and policy optimization
• Work on sim-to-real transfer and policy robustness
• Build software infrastructure for large-scale training, evaluation, and experimentation
• Analyze policy behavior and failure modes to drive continuous improvement
• Integrate learned policies with robotics and control systems
• Collaborate with simulation, controls, and robotics engineers to deploy learned behaviors on hardware
• Contribute to scalable approaches for acquiring new manipulation capabilities

What We're Looking For

Required:

• Degree in Computer Science, Robotics, AI, Electrical Engineering, or related field
• Strong software engineering skills in Python and preferably C++
• Hands-on experience with reinforcement learning and deep learning
• Strong understanding of RL concepts: policy optimization, value functions, exploration, reward design
• Experience with PyTorch or similar deep learning frameworks
• Experience working with robotic systems and simulation environments
• Solid understanding of robot kinematics, dynamics, and control
• Strong analytical and problem-solving abilities
• Hands-on mindset and enthusiasm for testing learning algorithms on real robotic systems

Bonus:

• Experience with dexterous manipulation, grasping, or robotic hands
• Experience with sim-to-real reinforcement learning
• Familiarity with PPO, SAC, or other modern RL algorithms
• Experience with Isaac Lab, Isaac Sim, MuJoCo, or similar simulation platforms
• Experience with distributed or large-scale RL training

Location: Munich. This role requires close collaboration with hardware and engineering teams.

How We Work with You

Candidates apply directly through Get A Job.ai. Our recruiting team will conduct an initial screen to understand your background and fit for the role. If there's a strong match, we'll submit your profile to our client for consideration. Please do not contact the client directly—all communication flows through our talent team to ensure a professional, coordinated process.

Pay

Compensation details will be discussed during the screening process based on experience and qualifications.

Get A Job.ai is an equal opportunity recruiter. We welcome applications from candidates of all backgrounds and do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.