Responsibilities
Designing and implementing machine learning models for forecasting, optimization, and control of distributed energy assets
Productionizing ML models: from research to robust, scalable, real-time systems
Building and maintaining ML infrastructure and data pipelines (training, inference, monitoring, retraining)
Collaborating closely with energy experts and product teams to translate real‑world constraints into deployable algorithms
Developing backend software that integrates AI models into their orchestration platform
Improving system performance, reliability, and observability in mission‑critical environments
Profile
Solid experience as an Machine Learning Engineer, Applied Scientist, or Software Engineer with strong ML exposure
Proven ability to deploy ML models into production systems, not just notebooks
Good knowledge of Python, data & streaming, MLOps and cloud infrastructure
Experience with time‑series data, optimization problems, or real‑time decision systems
Exposure to Data Science
A pragmatic mindset: you care about solutions that work in the real world
Clear communication and a collaborative approach
Experience in energy systems, energy data, IoT, or large‑scale optimization is a bonus
Additional Details
SENIORITY: Medior/Senior
START DATE: March
DURATION: 12 Months
EXTENSION: Yes
CONTRACT: Freelance
LOCATION: Antwerp
ONSITE POLICY: ~2 days per week (or equivalent each month)
HOURS PER WEEK: 40
LANGUAGES: Fluent English
INTERVIEW PROCESS: 2 stages
If you are interested, please forward your updated resume to to be considered.
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