Machine Learning Engineer
Role details
Job location
Tech stack
Job description
We are looking for a versatile machine learning engineer who can solve hard problems in code elegantly and efficiently. Your focus will be on the control algorithms of our Energy Management System. Part of the control algorithms could also be developing algorithms that enable us to trade electricity. You will be working closely together with the cloud developers in order to get your algorithms into production.
You need to have an intrinsic sense of curiosity and a huge sense of adventure as we are entering uncharted territory. Smartening our electricity grids will accelerate the energy transition and will make it more economical than many realize.
Responsibilities
- Developing event-driven lego blocks of code that perform flexible asset planning, energy trading and more.
- Use statistics and data insights to improve or develop new control algorithms.
- Create and maintain a simulation model to test new control algorithms.
- Creating resilient, reliable, and efficient software.
- Be responsible for running your code in production.
- Striking a balance between constant improvement and speed of development.
- Share knowledge with your colleagues.
- Curiosity in the fields of AI and what it can do for our control algorithms
Requirements
- Knowledge of efficient planning and/or optimization algorithms.
- Forecasting and planning is done in Python, experience is desirable.
Benefits & conditions
- Not fearing other programming languages: Most other parts of our platform are coded in Rust, which you might look at every now and then.
- General comprehension of electricity markets is favorable.
- Engage in discussions on functionality and quality, and actively seek collaboration.
- Be in our office at least two days per week and be based in the Netherlands.
- Speaking Dutch is an advantage.
- Wholeheartedly support the energy transition.
Compensation plan
Competitive salary package including a solid share-based component to benefit from the potential upside. Besides, we offer travel compensation for commuting and customer visits. Also, compensation for courses to improve your skills (including soft skills). Wednesday, Thursday, or Friday drinks with your colleagues and a remarkable yearly trip with the whole team.