Machine Learning Engineer - Energy Management

The Machine Learning Engineer at Eneco plays a pivotal role in accelerating the energy transition, aiming for climate neutrality by 2035. Within the Energy Management Systems domain, the team develops reliable, scalable, and intelligent data-driven solutions. This role involves owning the complete machine learning lifecycle, from scalable data processing and model training to production deployment and monitoring. Key responsibilities include designing and maintaining end-to-end ML pipelines for training, validation, and inference in batch and real-time environments, developing MLOps capabilities (CI/CD, automated testing, model versioning, drift detection, rollback mechanisms), and optimizing ML workloads on AWS. The role also involves building feature engineering pipelines, data contracts, and comprehensive monitoring/alerting systems for model performance and data/model drift. Close collaboration with Data Scientists and Data Engineers is essential to productionize models and continuously improve deployed solutions.