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3 дня назад

Data & ML Engineer – eMobility (SaaS)

Формат работы
hybrid
Тип работы
fulltime
Грейд
middle
Английский
b2
Страна
Netherlands
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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TL;DR
Data & ML Engineer – eMobility (SaaS) (Python/ML, EV Charging): Building data pipelines and prediction models for individual EV charging behaviour and aggregated flexibility delivered to energy markets with an accent on high-volume data, model reliability, and production deployment. Focus on designing model-ready datasets, monitoring data quality, integrating models into a .NET platform, and forecasting charging and grid flexibility.

Location: Arnhem, Gelderland, Netherlands; hybrid, with an average of 2 days per week at the Arnhem office. The role is not fully remote.

Company

hirify.global develops SaaS infrastructure for EV charging, payments, and grid flexibility across Europe.

What you will do

  • Design and build data pipelines from raw charging and market data to model-ready datasets.
  • Monitor data quality and identify issues before they affect models.
  • Develop prediction models for driver behaviour, charging sessions, and aggregated flexibility.
  • Deploy models to production when they outperform existing solutions.
  • Collaborate with C#/.NET developers to integrate and monitor models in the platform.

Requirements

  • 3+ years of experience building data pipelines on high-volume data and putting prediction models into production.
  • Strong data rigour, including testing assumptions and assessing prediction reliability.
  • Ability to investigate open questions, interpret data, and turn findings into clear technical and business decisions.
  • Daily working English is required.
  • Python and its data and ML stack, SQL, cloud model deployment, Git, and pull requests.
  • Curiosity about AI coding tools.
  • Ability to work with changing plans, take initiative, communicate disagreement constructively, and accept direct feedback.

Nice to have

  • Dutch.
  • Probabilistic forecasting.
  • Azure and Bicep.
  • Experience in energy markets, EV charging, or battery optimisation.

Culture & Benefits

  • Five-week Shape Up cycles with clear goals and autonomy over implementation.
  • Open contracts, roadmaps, and numbers, with ownership of outcomes and direct feedback.
  • 8% holiday allowance, 25 vacation days, and a pension.
  • €2,000 annual training budget and a choice of laptop.
  • 40 hours per week, or 36 hours by preference; regular office attendance in Arnhem is expected.

Hiring process

  • Introductory call with People & Culture, followed by a meeting with the Team Lead.
  • Approximately one-hour case, meeting with the Head of Engineering, and offer.
  • A short personality test is used as a conversation starter.

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