Machine Learning Engineer

About The Position You will work at the intersection of research and engineering, contributing to the development of AI systems applied in renewable energy and infrastructure environments. The role involves transforming data into forecasting, optimization, and decision-making systems, with a strong focus on deployment readiness and integration into operational workflows. You will collaborate with research, engineering, and innovation teams to deliver pilot-ready solutions aligned with real-world constraints, regulatory environments, and enterprise systems. ‍ Job responsibilities Design, develop, and optimize machine learning models for forecasting, optimization, and classification tasksBuild and maintain data pipelines for ingesting, processing, and validating data from multiple sourcesDeploy models into production environments, ensuring scalability, reliability, and performanceCollaborate with engineering teams on system architecture and API integrationValidate model performance using real-world datasets and operational metricsContribute to system documentation, testing frameworks, and continuous improvement processesSupport pilot deployments and monitor system behavior in operational environments Requirements Strong experience with Python and machine learning frameworks (e.g., TensorFlow, PyTorch, Scikit-learn)Experience working with real-world data pipelines and data processing systemsUnderstanding of model deployment, APIs, and cloud-based infrastructureFamiliarity with time-series data, forecasting, or optimization problemsAbility to work across research and engineering boundariesStrong problem-solving skills and attention to detail ‍