Skills this job asks for
PythonBudgetingStatisticsData engineeringCommunicationEnglish
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- Employer is on a government sponsor record
- This employer is on the IND public register of recognised sponsors. Source: Public register of recognised sponsors (Immigration and Naturalisation Service (IND)).
- Can’t check pay against the visa rules
- No salary stated. Netherlands highly skilled migrant permit needs at least €71,304 a year (under-30: €52,284). Source: https://ind.nl/en/required-amounts-income-requirements, rules effective 2026-01-01.
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About the role
Role - Software Engineer - Optimisation Team
Company - iwell - Harmonizing Clean Energy
Location - Utrecht
About iwell
At iwell, we are all about reinforcing energy security. We help European businesses become more energy independent. With growing regulations, extreme price volatility and rising grid issues, they need to be resilient. It is time to take charge and think ahead.
We deliver energy management solutions that ensure that businesses are always in control of their energy. Our in-house developed EMS and modular battery storage drive profit through sustainability, making businesses future-proof.
We are a fast-growing international team of bold, talented individuals. From engineers and software developers to creative thinkers and customer-focused business developers. No matter what your strong suit is, we always are looking for people who are determined to make a positive impact.
The Role
The Optimisation team builds the Python applications that decide what our customers' energy assets should do, and when. Batteries, EV fleets, solar and grid connections all come together in our optimiser, and the team turns prices, forecasts and constraints into schedules and decisions that run in production every day.
Much of this work has an operations-research flavour, and the problems rarely arrive neatly defined.. They arrive as a customer who needs their vans charged by 6:00 at the lowest cost or a battery whose value depends on the hour. We're looking for someone who is comfortable across that whole path: understanding the real-world problem, shaping it into something a computer can solve, and shipping and operating the result. You don't need to be an OR specialist. You do need to be a strong Python engineer who enjoys messy, concrete problems.
Success in this role means being able to:
• Take a loosely defined operational problem and turn it into working, maintainable production code.
• Work with data and models (optimisation, forecasting or plain statistics) without losing sight of the engineering.
What you will do
• Create charging schedules for EV fleets that minimise electricity costs while guaranteeing every vehicle is ready when it needs to be. This means modelling tariffs, grid limits and departure times, and handling what happens when reality deviates from the plan.
• Calculate the value of each kWh produced or consumed, so that batteries, solar and flexible loads are steered by what energy is actually worth at that moment, and customers can see where their savings come from.
• Build forecasting models that predict operational issues before they happen, to maximise asset uptime and reduce the number of support tickets our Operations team has to handle.
• Take your work all the way to production: packaging, deployment, monitoring and bugfixing.
• Work with the rest of the Optimisation team on the shared tooling, data pipelines and modelling conventions the team uses..
What are looking for
• 5+ years of production Python development experience, writing clean, tested, maintainable code.
• A proven ability to translate real-world problems into working code.
• A pragmatic mindset: you choose the boring, well-understood solution when it's the right one, and you know when it isn't.
• Strong communication skills and a habit of documenting your work. Fluency in English is required.
• Weekly working hours of 32-40 hours
• Coming into the office 3-4 days per week
Bonus points for
None of these are required. We'd rather hire a strong engineer and teach the domain than the other way around.
• Experience with a modelling library such as cvxpy or Pyomo, or other operations research experience..
• Time-series forecasting in production, or basic MLOps: keeping models trained, monitored and honest.
• Data analysis experi
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