Senior ML Engineer, Energy Forecasting

Job Description Senior ML Engineer, Energy Forecasting in Utrecht The Netherlands is currently facing one of the biggest energy transition challenges in Europe. The rapid growth of renewable energy sources such as solar and wind has fundamentally changed the stability of the energy grid. You will help build the intelligence layer behind renewable energy optimization, automated energy trading, and grid balancing. Your models will directly influence how renewable energy assets are forecasted, traded and optimized in real time. Every improvement in forecasting accuracy can have a measurable impact on profitability, operational efficiency and energy grid stability. The opportunity Balanz Energy is looking for a Senior ML Engineer, Energy Forecasting who wants to work at the intersection of machine learning, weather intelligence, renewable energy and large scale data processing. You will build production grade forecasting systems that process weather data, market data, asset telemetry and operational signals to support real time decision making. The environment combines machine learning, weather forecasting, automated trading infrastructure, distributed systems, data engineering, and software craftsmanship. Balanz Energy Balanz Energy is building the next generation infrastructure behind renewable energy optimization and automated energy trading. Production is increasingly weather dependent, while consumption patterns follow different cycles throughout the day and throughout the year. The company helps renewable energy providers optimize their assets through forecasting, market intelligence, automated trading strategies, and asset level optimization. Balanz Energy works from the asset level upwards. By understanding the exact behaviour of individual assets, the platform can make faster and more accurate decisions regarding forecasting, trading, curtailment, and optimization. The company recently went live in the Dutch market and is already working with a rapidly growing customer base. Engineering and AI philosophy The company intentionally keeps teams small, highly capable, and focused on ownership. AI is fully embedded into the development workflow. Engineers actively use modern AI tooling and coding agents to accelerate delivery and increase productivity. Success in this environment requires more than model building. It means understanding data quality, validating assumptions, making architectural decisions, measuring business impact, and operating reliable systems in production. Technical landscape The current environment includes Python as the primary machine learning language alongside modern forecasting and machine learning frameworks. The infrastructure stack includes Kubernetes, PostgreSQL, ClickHouse, Redis, NATS Jetstream and cloud native technologies for scalable model deployment and data processing. The platform processes large volumes of weather forecasts, energy market information, telemetry streams and operational data. The technology landscape continues to evolve together with product growth and forecasting requirements. What you will do Design and deploy forecasting models for renewable energy production, energy consumption, weather conditions, and asset performance Build end to end machine learning pipelines from data ingestion through production deployment and monitoring Process and analyse large scale datasets from weather APIs, numerical weather prediction models, sensor networks, market feeds, and operational systems Develop forecasting solutions using modern approaches such as Transformers, Graph Neural Networks, probabilistic forecasting, and spatio temporal modeling Improve model performance, scalability, interpretability, and operational reliability Collaborate closely with software engineers, energy analysts, and business stakeholders Help shape the machine learning architecture and forecasting strategy of the platform Contribute to testing, observability, and MLOps practices across the organization What Balanz Energy is looking for The company is looking for engineers who combine strong machine learning expertise with software engineering discipline and product ownership. Candidates should have deep experience with forecasting problems, large scale datasets, and production machine learning systems. Required experience 5+ years of experience in Machine Learning, Applied AI, Data Science, or a related field Strong Python experience Deep expertise in time series forecasting and predictive modeling Experience with weather forecasting, renewable energy forecasting, load forecasting, or similar forecasting domains Experience building production machine learning systems Experience building data pipelines from scratch Experience working with large scale datasets and distributed processing environments Experience with PyTorch, TensorFlow, NumPy, and modern ML tooling Experience deploying machine learning solutions using Docker and Kubernetes Strong understanding of software engineering principles, testing, and maintainability Nice to have Experience with numerical weather prediction data Experience in energy trading or energy markets Experience with Graph Neural Networks and Transformer based forecasting architectures Experience with geospatial data, satellite imagery, or remote sensing Experience with Spark, Ray, Kafka, or Flink Team and culture The company prefers teams to work together in person due to the complexity of the domain and the importance of fast communication and shared ownership. The office is located in Utrecht Flexibility exists for personal situations The culture is entrepreneurial, direct, technically driven, and collaborative Engineers are encouraged to think beyond models and contribute to the broader direction of the platform Relocation and visa sponsorship Candidates currently residing within the European Union are strongly encouraged to apply. Relocation support to the Netherlands is available for candidates relocating from within the EU. For exceptional candidates with highly relevant experience in energy forecasting, weather modeling, or large scale machine learning systems, visa sponsorship may be considered on a case by case basis. Compensation and benefits Balanz Energy offers a competitive and market aligned compensation package. This includes: Great salary package Bonus structure Pension contribution 33 vacation and ADV days Travel reimbursement Relocation support + visa sponsorship support where applicable Interview process Introductory conversation Technical machine learning and architecture discussion Practical forecasting and problem solving session Final culture and team fit discussion