Senior Machine Learning Engineer

Dexter energy services - Fulltime - amsterdam
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Dexter is a scale-up company from Amsterdam helping energy companies to make the energy transition towards a cleaner energy future more affordable. We do this by providing power forecasts and trading algorithms to optimize the short-term trading cycle and therefore enable the system to handle more renewable power.

Job Description

Our first products are live and successful and we are gaining momentum. We are now looking for an experienced Machine Learning Engineer with in-depth theoretical machine learning knowledge and a track record of converting this into production scale software. As you join our team of curious, ambitious and bright people, you will build new forecasting algorithms that will have an impact on the energy transition. If you are self-sufficient and have experience in time-series forecasting, then this job is for you.

Something about you

  • MSc or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field, or equivalent practical experience.
  • At least three years of experience in a Machine Learning role.
  • You are motivated to contribute to our mission and are keen to hear more about it.
  • You are excited about working with big time-series datasets.
  • Python is our tool of choice. To be more precise: we work on GCP with Python, Tensorflow, PyTorch, Pandas, Bokeh, Scikit, Kubernetes, Docker, Airflow,  SQL and NoSQL databases. Having experience in software engineering and productionising data products is required.
  • Domain knowledge in energy is a plus.
  • Having worked in a senior level role before will help too.

Other jobs at Dexter

No other jobs at this moment.

 

What we can offer you

Work in clean-tech and have an impact on the environment.

Build a cool company in a highly motivated and entrepreneurial team.

Low hierarchy and quick decision making.

Open culture where learning quickly is key.

The most modern stack (all our microservices run natively on managed kubernetes), epic CI/CD (all repos have automated testing and deployment set up), all code has documentation, and more best practices.

All our applications run natively on managed Kubernetes, and are set up as microservices, whose docker images are being built on every push in our ci/cd pipeline. We follow best practices to the bone.

Something about us

  • We are a clean-tech scale-up from Amsterdam.
  • Our goal: Create awesome software and algorithms that accelerate the energy transition. We do that by using machine learning and cloud technology to provide data services to energy companies.
  • We are still small and agile and aim for scalable products. We believe that our clients find our personal and custom-made approach vital. This means lots of responsibility and a can-do-mentality.
  • We are very ambitious, and we like to play. Therefore we encourage you to plan work around the hobbies you want to pursue.
  • Here’s a bit more about Dexter and what we do and who we are.

    What you will be doing

    Your focus will be on designing and implementing ML algorithms, such as time series forecasting, short-term weather forecasting and asset optimization.

    You should be able to build robust, automatic and scalable products to forecast short-term electricity prices, sustainable energy production and electricity consumption. Haven’t done that yet? No problem, we’ll show you.

    You will write most of your code in Python. Next to testing and building models you will build API connections and create workflows in Airflow. This can change from week to week as we build what needs to be built, based on your and our insights and based on what our customer needs.

    Customer delivery and therefore pragmatism is our number one priority. Directly after that comes building a scalable product. Wherever possible, you will build our system with lego blocks that can be reused in other projects.

    You will be working closely together with our CTO and the software developers. We are organised in autonomous and multidisciplinary product teams. For this more senior role we expect to contribute to multiple products.