Data Scientist, Reinforcement Learning

22.4k - 28.8k PLN22 400 - 28 800 PLN/ mies./ mies.B2BB2B (netto)

SeniorZdalnie·WrocławFull-time·B2B

#472501·Dodano dziś·2

Źródło: justjoin.it

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Tech Stack / Keywords

Reinforcement LearningDeep Reinforcement LearningMathematical OptimizationPython PyTorch Machine LearningsimulationDeep Learning NumPy TensorFlow

Podsumowanie oferty

As a Data Scientist, you will develop and improve Reinforcement Learning models for an Energy Management System (EMS) that optimizes energy flows and battery operations. You will combine machine learning with mathematical optimization and simulation for commercial and industrial energy management.

Wymagania

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.

Obowiązki

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.

Benefity

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.

KYOTU Technology

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