Senior ML Engineer, Energy Forecasting

Senior ML Engineer, Energy Forecasting | Utrecht, Netherlands
Onsite position – 4 days in the office per week.

What if your machine learning models directly influenced how renewable energy is traded, optimized, and forecasted?

Balanz Energy is building the intelligence layer behind renewable energy optimization and automated energy trading. We help renewable energy providers make better decisions through forecasting, market intelligence, and asset-level optimization.

We are looking for a Senior ML Engineer, Energy Forecasting to help build and scale forecasting systems that process weather data, energy market information, telemetry streams, and operational data in real time.

This role is ideal for someone who enjoys solving complex forecasting challenges and wants to work at the intersection of machine learning, weather intelligence, energy systems, and large scale data processing.

You will work on:

Renewable energy production forecasting

Weather modeling and prediction

Modern forecasting architectures, including Transformers and Graph Neural Networks

Build end-to-end machine learning pipelines from data ingestion through production deployment and monitoring

Required experience

5+ years of experience in Machine Learning, Applied AI, Data Science, or a related field

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, Tensor Flow, Num Py, 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

We are particularly interested in people with experience in:

Weather forecasting

Energy forecasting

Direct impact on the energy transition

Small engineering team with high ownership

Challenging technical problems

Competitive salary, bonus, pension, and 33 vacation days

Candidates across the European Union are encouraged to apply.

Relocation support is available and visa sponsorship may be considered for exceptional candidates with highly relevant experience.

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