Senior Robotics RL Engineer

Technology Innovation Institute; Dubai; On-site; AED 130,000 - 190,000; Full time

Job summary

Technology Innovation Institute (TII) is a publicly funded research institute in Abu Dhabi, UAE, renowned for robotics & AI research. We seek a Senior Reinforcement Learning Engineer to develop and deploy RL for robotics, UAV swarms, and distributed control, bridging theory with real-world deployments.

The candidate will design novel RL architectures, integrate advanced methodologies, and build scalable systems for complex control problems, collaborating with the Robotics Research Center.

Qualifications

• Master’s or PhD in CS/Robotics/AI/ML with RL focus.
• Proven RL work for robotics or UAVs.
• Strong multi-agent and swarm robotics expertise.
• Bridge between simulation and real-world deployment.

Responsibilities

• Design, implement, and optimize RL algorithms for robotic platforms and UAV swarms.
• Develop scalable training pipelines and sim-to-real transfer.
• Research and evaluate state-of-the-art RL methodologies.
• Collaborate with robotics middleware such as ROS2 and PX4.

Skills

Reinforcement Learning Expertise

Policy-gradient methods

Q-learning

Actor-critic frameworks

MARL

Federated learning

Centralized vs decentralized control

Memory-augmented policies

Sim2real techniques

Domain randomization

Transfer learning for robotics

Ray RLlib

Stable Baselines3

PyBullet

Isaac Gym

Gazebo

MuJoCo

AirSim

PyTorch

TensorFlow

JAX

Python

C++

ROS2

PX4

MAVSDK

Docker

distributed training systems

GPU clusters

CUDA

Education

Master’s or PhD in Computer Science, Robotics, AI/ML, or related field

Tools

ROS2

PX4

MAVSDK

Ray RLlib

Stable Baselines3

PyBullet

Isaac Gym

Gazebo

MuJoCo

AirSim

PyTorch

TensorFlow

JAX

Python

C++

Docker

Job description

Job Description:

Technology Innovation Institute (TII) is a publicly funded research institute, based in Abu Dhabi, United Arab Emirates. It is home to a diverse community of leading scientists, engineers, mathematicians, and researchers from across the globe, transforming problems and roadblocks into pioneering research and technology prototypes that help move society ahead.

This role is part of TII’s Robotics Research Center.

Job Description – Senior Reinforcement Learning (RL) Engineer

Position OverviewWe are seeking a talented Reinforcement Learning Engineer with expertise in developing

and deploying RL solutions for robotics, swarm intelligence, and drone systems. The

ideal candidate will have a strong foundation in both the theoretical RL and the practical

implementation of algorithms in real-world environments. You will design novel RL

architectures, integrate advanced methodologies and build scalable systems capable of

handling complex distributed control problems.

Key Responsibilities

• RL Algorithm Development & Integration: Design, implement, and optimize RL algorithms for robotic platforms, UAV swarms, and autonomous agents. Integrate and implement RL solutions for long-horizon planning and decision-making.
• Multi-Agent Reinforcement Learning (MARL): Build and evaluate MARL frameworks for coordination, deconfliction, and cooperative decision-making in multi-drone systems.
• Engineering & Deployment: Implement efficient training pipelines for large-scale RL simulations, optimize performance in simulation-to-real transfer for robotics and aerial vehicles
• Research & Innovation:Stay up to date with state-of-the-art RL methodologies Investigate hybrid learning paradigms (e.g., neurosymbolic methods, modelbased/model-free hybrids).
  

Core Competencies

• Reinforcement Learning Expertise
• Strong understanding of policy-gradient methods, Q-learning, actor-critic frameworks, and hierarchical RL.
• Hands-on experience with MARL, federated learning, centralized vs decentralized control, and memory-augmented policies
• Knowledge of sim2real techniques, domain randomization, and transfer learning for robotics.
• Development Tools & Libraries
• RL frameworks: Ray RLlib, Stable Baselines3, and others.
• Simulation environments: PyBullet, Isaac Gym, Gazebo, MuJoCo, AirSim.
• AI frameworks: PyTorch, TensorFlow, JAX.
• Programming Skills
• Python – primary language for RL research, prototyping, and experimentation.
• C++ – for performance-critical components, robotics middleware integration (e.g., ROS2), and real-time control.- Systems & Infrastructure
• Proficiency with Docker, distributed training systems, and GPU clusters.
• Familiarity with CUDA, and large-scale simulation pipelines.
• Experience deploying RL models in robotics middleware (ROS2, PX4, MAVSDK).

Qualifications

• 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.
• Excellent problem-solving ability and research-driven mindset.

Preferred (Nice-to-Have)

• Experience with safety-aware or constrained RL for critical systems.
• Background in distributed optimization, graph-based learning, or networked

systems.

• Contributions to open-source RL or robotics frameworks.
• Publications in AI/robotics conferences

At TII, we help society to overcome its biggest hurdles through a rigorous approach to scientific discovery and inquiry, using state-of-the-art facilities and collaboration with leading international institutions. Our rigorous discovery and inquiry-based approach helps to forge new and disruptive breakthroughs in AI, advanced materials, autonomous robotics, cryptography, digital security, directed energy, quantum computing and secure systems.

Requirements: