Your mission

• Research and prototype novel RL algorithms (e.g. exploration, POMDPs, multi-agent systems)
• Translate theory into scalable systems with support from our engineering teams
• Design experiments to test RL methods in complex environments (simulated or real)
• Collaborate with simulation, autonomy and AI infrastructure teams
• Contribute to strategic thinking around intelligent behavior and decision 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, AISTATS, ECML, etc. are a plus
• You think rigorously and build practically

• Experience with game theory, bandits, transfer learning or meta-learning

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.