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Location
Montreal, Quebec, Canada
Posted
July 17, 2026

Job Description

Job Description

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.

Key Responsibilities

  • 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 (, PPO, SAC, or Offline RL) capable of handling high-dimensional 3D observation spaces.
  • Sim-...

    • Job Details

    • Job Type
      Full-time
    • Category
      Computer Occupations
    • Date Posted
      July 17, 2026
    • Application Deadline
      August 26, 2026