Reinforcement Learning Robotics Engineer

About the role

The Technology Innovation Institute is seeking a Reinforcement Learning Engineer to develop and deploy RL solutions for robotics, swarm intelligence, and drone systems within its Robotics Research Center.

Key responsibilities

• Design, implement, and optimise RL algorithms for robotic platforms, UAV swarms and autonomous agents.
• Build and evaluate multi‑agent reinforcement learning frameworks for coordination and cooperative decision‑making in multi‑drone systems.
• Develop efficient training pipelines, manage large‑scale simulations and optimise sim‑to‑real transfer for robotics and aerial vehicles.
• Stay current with state‑of‑the‑art RL methodologies and investigate hybrid learning paradigms.

Required profile

• Master’s or PhD in Computer Science, Robotics, AI/ML or related field.
• Proven track record of implementing RL algorithms for robotics or UAV applications.
• Strong expertise in multi‑agent systems, swarm robotics and real‑world control.
• Experience bridging simulation and real‑world deployment.

Required skills

• Python and C++ programming.
• RL frameworks: Ray RLlib, Stable Baselines3.
• Simulation environments: PyBullet, Isaac Gym, Gazebo, MuJoCo, AirSim.
• AI frameworks: PyTorch, TensorFlow, JAX.
• Docker, distributed training systems, GPU clusters, CUDA.
• Robotics middleware: ROS2, PX4, MAVSDK.