Machine Learning Engineer

Role Overview

You will work at the intersection of research and engineering to develop AI systems for renewable energy and infrastructure settings. The focus is turning data into forecasting, optimization, and decision-making solutions that are ready to deploy and fit into operational workflows and enterprise systems.

Responsibilities

• Design, develop, and optimize machine learning models for forecasting, optimization, and classification
• Build and maintain data pipelines to ingest, process, and validate data from multiple sources
• Deploy models to production, ensuring scalability, reliability, and performance
• Collaborate with engineering teams on system architecture and API integration
• Validate model performance using real-world datasets and operational metrics
• Contribute to system documentation, testing frameworks, and continuous improvement
• Support pilot deployments and monitor system behavior in operational environments

Requirements

• Strong experience with Python and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn
• Experience working with real-world data pipelines and data processing systems
• Understanding of model deployment, APIs, and cloud-based infrastructure
• Familiarity with time-series, forecasting, or optimization problems
• Ability to work across research and engineering boundaries
• Strong problem-solving skills and attention to detail