Reinforcement Learning Engineer - Ingénieur(e) en apprentissage par renforcement

Design and build high-fidelity 2D/3D simulation environments to train reinforcement learning agents. Engineer reward functions and policy architectures, implement and optimize RL algorithms such as PPO, SAC, and Offline RL, and handle high-dimensional 3D observation spaces. Collaborate with ML, annotation, and TPM teams to align data, simulation, and training requirements, and close the sim-to-real “reality gap” using domain randomization and adaptation for reliable real-world performance.