Applied AI Scientist, Simulation & Reinforcement Learning

📋 Description

• Own and develop our SimPy-based discrete-event simulator, including its logic, design choices and
• Pay down technical debt: improve test coverage, code quality, reproducibility and developer tooling.
• Build the experiment infrastructure around the simulator: orchestration, study management
• Generate and maintain site data (e.g. distance files, configs) needed to simulate customer
• Support scenario testing and sensitivity analysis for our order-engine and orchestration teams.
• Define, measure and reduce the sim-to-real gap against real site data.

🎯 Requirements

• A PhD in Computer Science, AI/ML, Robotics, Mathematics, Physics, Operations Research or a related
• Hands-on experience building, extending or validating simulators, ideally discrete-event simulation
• Practical experience with reinforcement learning and training simulation-based agents, including
• Strong Python and software engineering fundamentals: testing, code review, maintainable and
• Rigorous experimental and statistical thinking: benchmarking, tuning, ablations, uncertainty.
• Experience in robotics, logistics, warehouse or other operations-heavy domains.