Senior machine learning engineer - energy forecasting.

You will work on models and pipelines that help make wind, solar and storage assets more predictable in European energy markets. If you enjoy applied ML with real operational impact, and you want to take ownership of forecasting systems rather than experiments only, this is the core of the role., * Design and implement machine learning models for forecasting weather conditions, renewable energy production and energy consumption patterns.

• Build and improve forecasting pipelines from data preparation and feature engineering to model validation, deployment and optimization.
• Work closely with data scientists, energy analysts and software engineers to improve datasets, labeling, model quality and operational usability.
• Apply modern time-series forecasting methods, such as Transformers, Graph Neural Networks, spatio-temporal models and probabilistic forecasting, where they add value.
• Optimize models for latency, performance and interpretability under high-frequency or large-scale data conditions.
• Translate business, market and environmental requirements into ML-driven insights that support operational decisions.
• Ensure data privacy, model security and compliance with applicable data standards and regulations. In deze baan vind je: Specialisme & Diepgang & Invloed Wat we bieden

You bring a strong applied ML background and the ability to move models into production. For this role, the core is forecasting expertise combined with solid software engineering practices.

• 5+ years of experience in applied Machine Learning or Data Science, with a strong focus on forecasting, modeling or energy analytics.
• An advanced degree, such as MSc or PhD, in Computer Science, Applied Mathematics, Statistics or a related field.
• Proven expertise in time-series forecasting and spatio-temporal modeling, ideally applied to weather or energy systems.
• Experience with numerical weather prediction data, satellite-based weather feeds and/or time-series based predictions.
• Strong Python skills, including libraries and frameworks such as Pandas, NumPy, PyTorch, TensorFlow, scikit-learn, Lightning or equivalent.
• A solid understanding of data engineering and ML infrastructure.
• Experience deploying ML models to cloud-native environments, such as Kubernetes, Docker, AWS, GCP or Azure ML pipelines.
• Experience with test-driven development and automated validation for ML models.
• Understanding of model performance optimization, for example GPU acceleration, model pruning, quantization or distributed inference.
• Excellent communication skills in English. Dutch is a strong plus.
• Experience in energy trading, renewable integration or grid forecasting is a plus.

• A senior ML role focused on forecasting systems for renewable energy and European power markets.
• The opportunity to work on production models that support decisions around wind, solar, storage and energy consumption patterns.
• Duration: 6 months initially. Upon satisfactory performance, the contract will be immediately converted to a permanent position.
• Probation period: not applicable.
• Location: Utrecht, with full-time office presence; no hybrid or remote work.
• Working hours: 38 hours per week plus 2 additional ADV leave hours.
• Holiday allowance: 8% of annual salary.
• Bonus scheme: 8% based on company performance and achievement of Balanz’s business objectives, plus 2% based on personal goals agreed upon with your manager.
• Vacation days: 21 vacation days and 12 ADV days per calendar year, with full salary.
• Sick leave: 100% salary during the first 6 months; thereafter 80%.
• Pension plan: employer contribution 8% and employee contribution 4%.
• Travel costs: public transport fully reimbursed; own transport reimbursed at €0.23 per kilometer.