Software Engineer bij Dexter Energy Services
The energy transition makes the electricity system more complex (unplannable renewable energy production, new consumption patterns like EV charging). To cope with this complexity, we provide energy companies with accurate forecasting of electricity production and consumption. Our solution is cloud-based and uses state-of-the-art machine learning technologies.
We improve and deploy our machine learning pipelines daily. As software developer you will help us build, maintain and scale these pipelines. If you are self-sufficient and have some experience in software engineering, then this job might be for you.
- Write clean, robust and scalable production code
- Handle data in an efficient and secure way
- Work closely with CTO and ML engineers
- Result-driven and pragmatic
- Like to work with the best tools (Google Cloud Platform, Kubernetes, GitLab, PyCharm)
- Tech stack: Docker, Python, Pandas, Scikit, Tensorflow, PyTorch
- Affinity with data, can work with SQL
- Interest in cleantech and energy transition
Something about us
- We create awesome technologies that accelerate the energy transition
- Small and agile team that builds scalable products
- We are ambitious but keep room for hobbies
What we can offer you
- Learn fast
- Work in clean-tech and create impact on environment
- Be part of an entrepreneurial team
- Low hierarchy
- Open culture
Dexter offers services to energy retailers and large-scale energy consumers to reduce power imbalance. The services consist of forecasting energy loads on asset-level or cluster-level as well as forecasting of short-term electricity prices. Additionally, Dexter unlocks flexibility by offering dispatching solutions to energy-related assets. On the demand side this means shifting energy loads to low-cost moments or to maximize the consumption of self-produced energy. This further reduces their energy bill while contributing to a more sustainable and flexible energy landscape. On the supply side, this is done by controlling the power output to contribute to grid stability. The algorithms built by Dexter use state-of-the-art machine learning technologies.