Senior Machine Learning Engineer

Balanz-Energy; Utrecht; On-site; EUR 60,000 - 90,000; Full time

Benefits offered by this job

21 vacation days

12 ADV days

8% Holiday Allowance

Public transport reimbursement

Job summary

Balanz-Energy in Utrecht is seeking a Senior Machine Learning Engineer to develop ML systems for time-series forecasting, focusing on renewable energy. You will collaborate with data scientists and engineers to create predictive models that inform key business decisions.

The ideal candidate has over 5 years of experience in Machine Learning, advanced degrees in relevant fields, and strong proficiency in Python libraries. This role requires full-time office presence with a range of employee benefits including vacation days and performance bonus.

Qualifications

• 5+ years of experience in applied Machine Learning or Data Science.
• Experience with numerical weather prediction (NWP) data.
• Experience deploying ML models to cloud-native environments.

Responsibilities

• Design and implement advanced ML models for forecasting.
• Collaborate with domain experts and data engineers.
• Optimize models for latency, performance, and interpretability.

Skills

Applied Machine Learning

Data Science

Forecasting

Python

Feature Engineering

Performance Optimization

Communication Skills

Education

Advanced degree (MSc/PhD) in Computer Science, Applied Mathematics, or Statistics

Tools

Pandas

NumPy

PyTorch

TensorFlow

scikit-learn

AWS/GCP/Azure

Job description

Your role

We are seeking a Senior Machine Learning Engineer with deep expertise in time-series forecasting, weather modeling, and renewable energy prediction. The ideal candidate will combine strong applied ML knowledge with robust software engineering practices to design, deploy, and optimize forecasting pipelines that drive key business and operational decisions. You will work closely with data scientists, energy analysts, and software engineers to deliver high-accuracy, scalable, and explainable ML systems. The ideal candidate thrives in a test-driven, data-intensive, and fast pacing environment, and has a strong focus on model performance, interpretability, and maintainability.

• Design and implement advanced ML models for forecasting weather conditions, renewable energy production, and energy consumption patterns.
• Collaborate with domain experts and data engineers to ensure high-quality datasets, robust feature engineering, and accurate labeling.
• Apply and extend state-of-the-art methods in time-series forecasting (e.g., Transformers, Graph Neural Networks, Spatio-Temporal models, probabilistic forecasting).
• Optimize models for latency, performance, and interpretability, particularly under high-frequency or large-scale data conditions.
• Collaborate cross-functionally to translate complex business and environmental requirements into actionable ML-driven insights.
• Ensure data privacy, model security, and compliance with applicable data standards and regulations

Your profile

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

What we offer

• Duration:
  • 6 months initially. Upon satisfactory performance, the contract will be immediately converted to a permanent position.
• Probation Period:
  • Not applicable.
• Location:
  • Utrecht (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.
  • 2% based on personal goals agreed upon with your manager.
• Company Regulations:
  • Will form part of the employment agreement; currently under development.
• 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%
  • Employee contribution: 4%
• Travel Costs:
  • Public transport: fully reimbursed.
  • Own transport: €0.23 per kilometer.

About us

Balanz is a next-generation energy trading company founded in 2025 with a clear ambition: to transform how renewable energy interacts with European power markets. Our mission is to empower wind, solar, and storage asset owners by giving them direct, intelligent access to energy markets through advanced technology and data-driven control systems.

We operate as a licensed Balance Responsible Party (BRP) and will soon expand into Balancing and Congestion Service Provider (BSP/CSP) roles. This means we don’t just trade energy—we actively manage imbalances, optimize flexibility, and create new revenue streams for our partners. Our first market entry will be in the Netherlands in 2026, followed by rapid expansion across Europe. Our long-term vision is to connect thousands of renewable assets and energy suppliers, making renewable energy predictable, profitable, and fully integrated into the power system of the future.