Machine Learning Engineer

Machine Learning Engineer at Vandebron

Who we are

At Vandebron, we're transforming the energy landscape, steering away from the conventional to champion sustainability. Born in 2014, our journey began with Chapter 1, disrupting the market with a transparent platform connecting consumers directly to local, green energy producers. Now, in Chapter 2, we are dedicated to ensuring 100% green energy availability, 100% of the time. Think smart solutions — flexible use of wind and solar farms, Smart EV Charging, and efficient energy storage.

No waiting around, we actively shape a sustainable future. Good energy, smart solutions, that’s Vandebron.

Your impact

You’ll join our Energy Forecasting & Trade Algorithms (EFTA) team — a tight-knit team at the core of Vandebron’s Producer domain. We create and operate mission-critical forecasting products and trading algorithms that empower data-driven decisions across energy markets.

As a Machine Learning Engineer, you’ll act as the bridge between our data scientists and engineers. You’ll bring machine learning models from concept to production, ensuring they are robust, scalable, and impactful in driving the energy transition forward. You’ll translate business needs into ML solutions, refine our Python codebase, and deploy and monitor models that forecast energy production, optimize trading strategies, and enable smarter energy management.

If you want to build real-world ML solutions that have a direct impact on making the energy sector greener — this is the role for you.

In this role you will be reporting to Tim Faber, Manager Data Analytics.

What you’ll do

• Translate business requirements into scalable designs for machine learning solutions.
• Implement ML solutions as Python modules and iterate on the existing ML codebase.
• Deploy and monitor machine learning models focused on energy forecasting, trading optimization, and related applications.
• Collaborate with engineers to elevate the quality, reliability, and scalability of our ML products.
• Manage and optimize ML orchestration tooling, ensuring reliable and timely model execution (e.g., using MLflow, Kubeflow, Dagster/Airflow).
• Actively share findings and knowledge across teams, contributing to a strong internal ML community.
• Stay ahead of the curve by continuously adopting new tools, techniques, and best practices to improve our ML operations.

What you bring

• 3+ years of experience as a Machine Learning Engineer working with machine learning pipelines.
• Solid experience in Python and proficiency with relevant data/ML libraries.
• Experience with time series forecasting.
• Strong background in MLOps principles and hands-on experience with tools like MLflow, Kubeflow, or similar.
• Practical experience with version control (Git), containerization (Docker), and orchestration frameworks like Dagster or Airflow.
• Experience in setting up and using CI/CD workflows for ML applications.
• Passion for the energy transition and a genuine interest in the real-world application of your work.
• Strong communication skills — you thrive in a close, collaborative team setting.
• Bonus: product development in the energy domain.

What’s in it for you

• A nice salary between €4.500,- and €5.400,- gross per month, based on 40 hours and excluding holiday allowance - based on experience.
• An annual bonus based on company performance.
• 30 paid days off per year to recharge and find inspiration.
• Two additional days: 1 for religious or personal celebrations and 1 volunteering day.
• Work abroad for up to 6 weeks per year (max 4 consecutive weeks, including up to 4 weeks outside the EU).
• A sabbatical opportunity after three years of service (one month paid with holidays, two unpaid).
• An €850 annual learning budget and access to Learning & Development programs.
• A pension scheme to plan for the future.
• A €50 net monthly reimbursement for phone and Wi-Fi costs.
• A one-time €200 net allowance to set up your home workspace.
• A hybrid work environment split between home and our carbon-neutral Amsterdam office. In this role, we expect you’ll be at the office 3-4 days per week.
• Daily healthy lunches by our in-house cooks.
• An NS business card for those commuting 10km or more.

Why join Vandebron?

• Work on impactful products — Your ML models will directly contribute to a greener energy system and a more sustainable future.
• Be part of a close, supportive team — Tight collaboration, smart colleagues, and autonomy where it counts.
• Develop your expertise — You’ll work on cutting-edge ML pipelines, contribute to the evolution of our forecasting capabilities, and extend your domain knowledge into areas like price forecasting and new markets.
• Join a mission-driven company — You’ll see the real-world impact of your work on the environment and society.

A career move that matters

Within 6–12 months, success in this role means:

• You’ve fully onboarded into the EFTA team and built strong working relationships with engineers and data scientists.
• You’ve added fresh ideas and meaningful contributions to improve our ML pipelines and processes.
• You’ve taken ownership of ML deployment and orchestration workflows, improving reliability and scalability.
• You’re actively shaping how we forecast, optimize, and trade green energy smarter every day.

If this role excites you, apply via this page.

Still have questions? Feel free to ask via tommythomassen@vandebron.nl.

At Vandebron, we believe in diversity, inclusiveness, and equal career opportunities. Be your authentic self — and it’s totally okay with us if you don’t mention your gender or date of birth on your resume. We also care about your privacy and handle your data carefully. Under the GDPR, you are not required to provide us with any information about your health, race/nationality, or religion, and you may also omit your social security number (BSN) and passport photo from your job application documentation.