You will design and improve machine learning models for time-series forecasting and nonlinear optimization, taking them from concept to deployment. * You bring a strong background in Python and machine learning engineering, with hands-on experience developing, testing, and maintaining models in containerized production environments (e.g., Docker, AWS). * You are familiar with the full machine-learning lifecycle, from training to deployment and monitoring, and you have experience using MLOps tools such as Prefect, MLflow, or similar platforms. As an ML Engineer, you'll support our Sector Coupling team building the next generation of intelligent Energy Management Systems (EMS). You will enable high-accuracy model predictions and optimizations through lo
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