Senior Machine Learning 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

• Energy consumption forecasting

• Weather modeling and prediction

• Large-scale machine learning pipelines

• Real-time decision support systems

• Modern forecasting architectures, including Transformers and Graph Neural Networks

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

Our environment includes:

• Python

• PyTorch

• TensorFlow

• Kubernetes

• PostgreSQL

• ClickHouse

• Redis

• NATS Jetstream

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

We are particularly interested in people with experience in:

• Time series forecasting

• Weather forecasting

• Energy forecasting

• Quantitative modeling

• Large-scale machine learning systems

• Production ML environments

Why join?

• Direct impact on the energy transition

• Small engineering team with high ownership

• Modern AI driven engineering culture

• 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.

Interested or know someone who could be a fit?