Senior RL Engineer - Ingénieur; e) principal; e) en apprentissage par renforcement

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Notre impact repose sur l’amélioration des communautés dans lesquelles vivent et travaillent nos employés, nos clients et nos publics. Nous avons une riche tradition d’engagement social et veillons à ce que nos employés aient la possibilité de s’investir au sein de leurs communautés. Nous défendons une culture inclusive et nous nous efforçons d’attirer et de former une main-d’œuvre talentueuse afin de créer et de proposer un large éventail de contenus reflétant notre monde.

We are seeking a Reinforcement Learning Engineer with experience manipulating virtual environments to train autonomous agents. This role focuses on the design of robust simulation environments, reward structures, and policy architectures that can navigate complex, multi-sensor landscapes.

• Cross-Functional Coordination:
  Work with partner ML and Annotation engineers and TPMs to spec out data, simulation, and training requirements.
• Environment Design:
  Build and maintain high-fidelity 2D/3D simulation environments (using tools like Unity, Unreal, or Isaac Sim) that serve as the training ground for RL agents.
• Reward Engineering:
  Design and tune complex reward functions that align agent behavior with product goals and safety constraints.
• Algorithm Implementation:
  Develop and optimize RL algorithms (e.g., PPO, SAC, or Offline RL) capable of handling high-dimensional 3D observation spaces.
• Sim-to-Real Strategy:
  Analyze the "reality gap" and implement domain randomization or adaptation techniques to ensure models perform reliably in real-world scenarios.

Nous sommes à la recherche d’un(e) ingénieur(e) en apprentissage par renforcement ayant de l’expérience dans la création et l’exploitation d’environnements virtuels pour l’entraînement d’agents autonomes. Ce rôle consiste à concevoir des environnements de simulation robustes, des structures de récompense et des architectures de politiques capables d’évoluer dans des contextes complexes et multi-capteurs.

Vous jouerez un rôle clé dans le rapprochement entre simulation et performance réelle en développant des systèmes RL évolutifs et en garantissant un comportement fiable des agents dans des conditions variées.

• Collaboration interfonctionnelle :
  Travailler avec les ingénieurs ML, les équipes d’annotation et les…