Remote Senior AI Engineer - Reinforcement Learning

About the Role Our client, a global leader in developing advanced AI solutions for complex decision‑making problems, is looking for a Senior AI Engineer specializing in Reinforcement Learning (RL). This is a fully remote position, allowing you to contribute to pioneering work from anywhere. You will be responsible for designing, implementing, and deploying sophisticated RL algorithms to solve challenging optimization and control tasks across various domains, such as robotics, gaming, and resource management.

The ideal candidate possesses a deep understanding of RL theory, extensive practical experience in applying RL techniques, and strong programming skills.

This role offers a unique opportunity to drive innovation in a critical area of artificial intelligence and work on highly impactful projects.

Key Responsibilities   Design, implement, and evaluate state‑of‑the‑art Reinforcement Learning algorithms.
Develop and maintain RL environments and simulation platforms.
Apply RL techniques to solve real‑world problems in areas such as control systems, optimization, and autonomous decision‑making.
Collaborate with cross‑functional teams to define project requirements and objectives.
Optimize RL agents for performance, stability, and efficiency.
Stay abreast of the latest research and advancements in Reinforcement Learning and related fields.
Contribute to the deployment and operationalization of RL solutions in production.
Write clean, well‑documented, and testable code.
Mentor junior engineers and contribute to the team's technical growth.
Communicate research findings and project progress to stakeholders.
Requirements   Master's or Ph.D. degree in Computer Science, Artificial Intelligence, Robotics, or a related quantitative field.
5+ years of experience in AI/ML, with a strong specialization in Reinforcement Learning.
Proven experience in applying RL algorithms (e.g., Q‑learning, Policy Gradients, Actor‑Critic) to practical problems.
Proficiency in Python and deep learning frameworks (e.g., Tensor Flow, PyTorch).

Experience with RL libraries and frameworks (e.g., Stable Baselines, RLlib) is a plus.
Strong understanding of mathematics, statistics, and optimization techniques.

Experience with simulation environments (e.g., OpenAI Gym, Mu Jo Co ) is advantageous.
Excellent problem‑solving, analytical, and algorithmic thinking skills.
Strong communication and collaboration skills, effective in a remote setting.
Demonstrated ability to lead technical initiatives.
Benefits   Highly competitive salary and significant bonus potential.
Fully remote work with flexible scheduling.
Comprehensive health, dental, and vision insurance.
Generous professional development budget and opportunities for growth.
Work on cutting‑edge RL projects with impactful applications.
Collaborative and intellectually stimulating remote work environment.
Paid time off and company holidays.
Retirement savings plan with company match.