Data Scientist, Reinforcement Learning

Location: 100% remote Contract type: B2B Capacity: Full-time Rate: 140-180 PLN + VAT / h

• About the project

We are looking for an experienced Data Scientist with a strong background in Reinforcement Learning to join an innovative project focused on intelligent energy management.

We are building an Energy Management System (EMS) that helps commercial and industrial facilities optimize how they consume, store, and manage electricity.

The system analyzes energy consumption, renewable energy production, electricity prices, and battery storage conditions to make smarter decisions about energy usage.

Your main challenge will be to develop and improve Reinforcement Learning models that optimize energy flows and battery operations, combining machine learning with mathematical optimization and simulation.

You will have the opportunity to experiment with different RL approaches, evaluate their effectiveness against optimization-based solutions, and contribute to building intelligent control strategies with measurable business impact.

We are specifically looking for someone with hands-on commercial experience in Reinforcement Learning. A background in traditional Machine Learning or Data Science alone will not be sufficient for this role.

• Who we are

Kyotu Technology is a boutique software house based in Wrocław and Warsaw, working fully remotely or in hybrid mode across Poland.

We focus on long-term, high-quality engineering and building complex, production-grade systems with real business impact. Our teams have real influence on technical and architectural decisions.

• Your responsibilities
• Design, train, evaluate, and improve Reinforcement Learning models for energy management and optimization
• Develop mathematical optimization models to benchmark and validate RL-based solutions
• Define RL environments, including reward functions, state and action spaces, and operational constraints
• Build and improve simulations of battery storage systems, photovoltaic installations, and energy flows
• Experiment with different RL algorithms and optimization approaches to identify effective control strategies
• Analyze agent behavior, troubleshoot training issues, and improve model performance
• Compare RL policies against mathematical optimization models and baseline strategies
• Test solutions across different energy consumption patterns, installation configurations, and market conditions
• Process and analyze energy consumption, renewable production, weather, and electricity pricing data
• Occasionally contribute to electricity price forecasting models
• Must haves

Reinforcement Learning & Optimization

• Commercial, hands-on experience developing, training, and evaluating Reinforcement Learning models
• Practical experience with RL algorithms, such as PPO, DQN, or similar approaches
• Ability to independently design RL environments, including reward functions, state representations, action spaces, and constraints
• Experience evaluating RL agent performance, debugging training processes, and improving policies
• Solid understanding of mathematical optimization, including objective functions, constraints, and optimization-based decision-making
• Ability to formulate optimization problems involving discrete and continuous variables
• Understanding of how mathematical optimization can be used to benchmark RL solutions

Machine Learning & Engineering

• Strong programming skills in Python
• Practical experience with PyTorch, TensorFlow, or similar ML frameworks
• Very good knowledge of pandas and NumPy
• Experience training, evaluating, and comparing Machine Learning models
• Experience deploying Machine Learning models into production environments
• Ability to design experiments, evaluate results, and identify opportunities for model improvement
• Experience writing clean, maintainable, and testable Python code
• Experience with Git
• Strong analytical and problem-solving skills
• Ability to work independently and take ownership of technical solutions
• English at B2 level or higher
• Nice to have
• Experience applying Reinforcement Learning to control systems, robotics, autonomous systems, or simulation-based optimization
• Knowledge of energy systems, renewable energy, battery storage, or electricity markets
• Experience with Gymnasium or TorchRL
• Knowledge of linear programming, MILP, or dynamic programming
• Experience developing simulation environments for RL agents
• Experience with time-series forecasting and architectures such as TFT or TiDE
• Familiarity with Optuna, DVC, or MLflow
• Experience working with energy consumption, weather, renewable production, or electricity pricing data
• Experience using AI coding assistants such as Claude Code or Codex
• Experience with Docker or Kubernetes
• What we offer
• B2B contract
• 140-180 PLN + VAT / h
• 100% remote work
• Full-time engagement
• Long-term cooperation
• Opportunity to work on a real-world project combining Reinforcement Learning, mathematical optimization, and energy technologies
• High level of independence and ownership
• Real influence on model development, experimentation, and technical decisions
• Opportunity to develop intelligent systems that help optimize energy costs and renewable energy utilization
• Collaboration with experienced engineering and AI/ML specialists