Reinforcement Learning (RL) Engineer - Robotics

About the role

The Technology Innovation Institute (TII), a publicly funded research institute in Abu Dhabi, UAE, is hiring a Reinforcement Learning Engineer for its Robotics Research Center. The role focuses on designing, implementing and deploying RL solutions for robotics, swarm intelligence and drone systems, including novel architectures and scalable systems for complex distributed control problems.

Key responsibilities

• Design, implement and optimise RL algorithms for robotic platforms, UAV swarms and autonomous agents, including long-horizon planning and decision-making.
• Build and evaluate MARL frameworks for coordination, deconfliction and cooperative decision-making in multi-drone systems.
• Implement efficient training pipelines for large-scale RL simulations and optimise simulation-to-real transfer for robotics and aerial vehicles.
• Stay up to date with state-of-the-art RL methods and investigate hybrid learning paradigms such as neurosymbolic and model-based/model-free approaches.

Required profile

• Master's or PhD in Computer Science, Robotics, AI/ML or a related field.
• Proven track record implementing RL algorithms for robotics or UAV applications.
• Strong expertise in multi-agent systems, swarm robotics and real-world control, with experience bridging simulation and real-world deployment.
• Excellent problem-solving ability and a research-driven mindset.

Required skills

• RL: policy-gradient methods, Q-learning, actor-critic, hierarchical RL, MARL, federated learning, sim2real, domain randomization, transfer learning.
• Frameworks: Ray RLlib, Stable Baselines3; PyTorch, TensorFlow, JAX.
• Simulators: PyBullet, Isaac Gym, Gazebo, MuJoCo, AirSim.
• Programming: Python and C++, ROS2, PX4, MAVSDK.
• Infrastructure: Docker, distributed training, GPU clusters, CUDA.

Nice to have: safety-aware or constrained RL, distributed optimization or graph-based learning, open-source contributions, conference publications.