Applied AI Scientist, Simulation & Reinforcement Learning
Core
Own and develop a discrete-event simulator (SimPy) to validate and train reinforcement learning policies for robot orchestration in warehouse operations.
Role type
Senior Applied AI Scientist (Simulation & Reinforcement Learning)
Builds
A trustworthy simulation environment for RL-driven robot orchestration frameworks
Domain
Robotics, Logistics, Warehouse Operations, Reinforcement Learning
Deliverable
production ML models
Required skills
Discrete-event simulation (SimPy), Reinforcement Learning, Python, Experimental design, Statistical analysis, Robotics domain knowledge
Preferred skills
Publications in top AI/ML venues, Multi-agent systems, Optimization (Optuna)
Technologies
SimPy, Gymnasium/Gym, Optuna, Python
Responsibilities
Own and develop the SimPy-based discrete-event simulator; Reduce the sim-to-real gap using real site data; Design, train, and evaluate RL policies; Build experiment infrastructure for automated runs; Prototype and productionize learning-based components.
Seniority
Senior, hands-on IC
