Reinforcement Learning Research Engineer - Exploration & Decision Intelligence

• 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

Do you have experience in Python?, 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.

We are a defence-tech start-up specializing in machine vision solutions. If you have a passion for cutting-edge innovation, and drive to use your skills to create next generation solutions, this is an opportunity for you! What we do: We are developing solutions that enable computers and sensors to collaborate as teams, working together to address emerging security challenges. Our primary mission is to defend against AI-powered asymmetric threats at scale, such as drone swarms and other UXVs. Who we are: Based in Munich, Berlin and Bordeaux/Toulouse we are rapidly expanding across Europe with plans to open more office hubs soon. We embrace a hybrid work culture - valuing the collaborations that happens in the office, while also empowering our team members to work remotely with responsibility and autonomy.