Reinforcement Learning (RL) Engineer (2 - 5 Years)

We are seeking a highly skilled Reinforcement Learning (RL) Engineer to develop, implement, and optimize RL algorithms for real-world and simulation-based applications. The ideal candidate has strong foundations in machine learning, deep learning, control systems, and hands-on experience deploying RL models in production or embedded systems.

Responsibilities

• Design, implement, and optimize RL algorithms such as PPO, SAC, TD3, DQN,A3C, TRPO, etc.
• Develop custom reward functions, policy architectures, and learning workflows.
• Conduct research on state-of-the-art RL techniques and integrate into productor research pipelines.
• Build or work with simulation environments such as PyBullet, Mujoco, IsaacGym, CARLA, Gazebo, or custom environments.
• Integrate RL agents with environment APIs, physics engines, and sensor models.
• Deploy RL models on real systems (e.g., robots, embedded hardware, autonom...