Reinforcement Learning Engineer (RL & Optimization)

Kyotu Technology is seeking a skilled Reinforcement Learning Engineer to join an innovative project focused on developing an intelligent Energy Management System (EMS). You will work on complex control strategies for battery storage and energy flows, utilizing a combination of reinforcement learning, mathematical optimization, and system simulation to reduce energy costs and maximize renewable energy usage.

Key responsibilities

• Designing, training, testing, and improving Reinforcement Learning agents and models.
• Developing mathematical optimization models to serve as benchmarks for RL-based solutions.
• Defining reward functions, state and action spaces, and decision constraints within RL environments.
• Developing and improving simulations for battery storage systems and energy flows.
• Analyzing agent behavior and identifying opportunities to improve model performance through experimentation.

Requirements

• Commercial, hands-on experience in developing, training, and evaluating Reinforcement Learning models.
• Practical experience with RL algorithms such as PPO or DQN and the ability to design custom RL environments.
• Solid understanding of mathematical optimization fundamentals and problem formulation.
• Strong proficiency in Python, including PyTorch, NumPy, and pandas.
• Experience deploying machine learning models into production environments and writing maintainable, testable code.

What we offer

• Fully remote work environment with full-time engagement.
• Long-term cooperation on a technically challenging project.
• High level of independence and ownership over technical and architectural decisions.
• Opportunity to work with experienced engineering and AI/ML specialists on impactful energy technology.