Senior Ai Research Engineer - Reinforcement Learning

About the Role

Our client is a leading AI research and development company seeking a Senior AI Research Engineer specializing in Reinforcement Learning (RL) to join their innovative team. This role is based in East London, Eastern Cape, ZA, and offers a fully remote working arrangement. You will be instrumental in pushing the boundaries of RL, designing and implementing advanced algorithms for complex decision-making problems. This is an exceptional opportunity to contribute to cutting-edge research, collaborate with world-class scientists and engineers, and make a tangible impact on real-world applications. As a remote-first company, we foster a highly collaborative and productive virtual environment, ensuring that all team members are connected and supported, regardless of their geographical location. This position requires a deep understanding of theoretical RL concepts and practical implementation skills.

Key Responsibilities

• Conduct advanced research in Reinforcement Learning, exploring new algorithms and techniques.
• Design, implement, and test RL agents for complex control and optimization problems.
• Develop and maintain high-performance RL simulation environments.
• Collaborate with cross-functional teams to apply RL solutions to various business challenges.
• Publish research findings in top-tier conferences and journals.
• Optimize RL algorithms for efficiency, scalability, and robustness.
• Mentor junior researchers and engineers in the field of RL.
• Stay abreast of the latest advancements in AI, machine learning, and reinforcement learning.
• Contribute to the strategic direction of the company's RL research efforts.
• Ensure code quality, documentation, and reproducibility of research experiments.

Requirements

• Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field with a specialization in Reinforcement Learning.
• Proven track record of research and development in RL, evidenced by publications in leading conferences (e.g., NeurIPS, ICML, ICLR) or significant industry contributions.
• Expertise in core RL algorithms (e.g., Q-learning, Policy Gradients, Actor-Critic methods) and their modern variations.
• Strong programming skills in Python and experience with deep learning frameworks (TensorFlow, PyTorch).
• Experience with RL libraries and simulators (e.g., Stable Baselines3, RLlib, OpenAI Gym).
• Excellent analytical and problem-solving skills.
• Ability to work independently and effectively in a remote research environment.
• Strong communication and collaboration skills.
• Experience with parallel computing and distributed systems is a plus.
• Knowledge of related fields such as control theory or optimization is beneficial.

Benefits

• Highly competitive salary and performance-based incentives.
• Comprehensive benefits package including health, dental, and vision insurance.
• Generous paid time off and flexible remote working options.
• Opportunities for continuous learning, professional development, and conference attendance.
• Access to significant computational resources for research.
• A vibrant and collaborative remote work culture that encourages innovation.
• Home office setup and technology support.
• Regular virtual social events and team activities.

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