AI/ML Engineer (Energy Forecasting)

AI/ML Engineer (Energy Forecasting)

Role Overview:

Our client, a leader in digital energy innovation and grid intelligence, is seeking an AI/ML Engineer (Energy Forecasting) to develop advanced models for predicting renewable generation, load demand, and market dynamics. This role is central to enabling data-driven decision-making across energy trading, grid operations, and asset optimisation.

Key Responsibilities:

• Design and implement machine learning models for short-term and long-term forecasting of solar, wind, and hybrid energy generation
• Develop predictive analytics for load forecasting, price forecasting, and grid congestion
• Work with large-scale time-series datasets from SCADA, weather APIs, and market platforms
• Collaborate with data engineers, energy analysts, and software developers to deploy models into production
• Continuously evaluate model performance and retrain using real-time and historical data
• Contribute to the development of digital twins, optimization algorithms, and AI-driven control systems
• Ensure model transparency, explainability, and compliance with regulatory standards

Essential Experience:

• Degree in Computer Science, Data Science, Electrical Engineering, or a related field
• 3–6 years of experience in AI/ML engineering, preferably in the energy or utilities sector
• Proficiency in Python, TensorFlow, PyTorch, scikit-learn, and time-series modeling techniques
• Experience with cloud platforms (AWS, Azure, GCP) and MLOps tools (e.g., MLflow, Kubeflow)
• Strong understanding of renewable energy systems, weather data, and grid operations

Desirable:

• Experience with probabilistic forecasting, ensemble models, or deep learning architectures (e.g., LSTM, Transformer)
• Familiarity with energy market dynamics, trading strategies, or demand response programs
• Knowledge of spatial-temporal modeling, satellite data, or geospatial analytics