Reinforcement Learning Research Engineer – Exploration & Decision Intelligence (m/w/d)

Autonomous Teaming

Munich (DEU) permanent

Posted: January 6, 2026

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Quick Summary

Design and implement reinforcement learning algorithms for edge devices, including exploration and decision intelligence, with a focus on scalability and collaboration with engineering teams.

Required Skills

Deep knowledge of RL theory Simulation-based learning Python proficiency Mathematics and statistics foundation Publications at top conferences

Job Description

Your mission:
• Research and prototype novel RL algorithms (e.g. exploration, POMDPs, multi-agent systems)
• Design and implement use-cases for DRL on edge devices
• Translate theory into scalable systems with support from our engineering teams
• Collaborate with simulation, autonomy and AI infrastructure teams
• Develop decision-making for intelligent behavior and architectures

Your profile:
• Deep knowledge of RL theory: policy gradients, value iteration, Q-learning, etc.
• Experience with simulation-based learning and probabilistic models
• Python proficiency; strong math/stats foundation
• Publications at NeurIPS, ICLR, ICML, ICRA, IROS, etc. are a plus
• You think rigorously and build practically

Nice to have:

• Experience of deploying AI models to real-life systems

Why us?:
Join us to shape the future of AI-driven defense!

Do you feel that you fit the description, but don't think you fulfill all the criteria 100%? Apply to us anyway. 
We look forward to receiving your detailed application via our online form. 

The world is changing. Exponential technologies are enabling new types of security threats. We are committed to staying ahead by building nimble, scalable, and cost-effective defences. We are looking for passionate developers who are eager to create exceptional products, safeguard our freedom, and strengthen the resilience of democracies.

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