Are you ready to use your MLOps expertise to help us unlock the power of ML models and bring them from research into operational use? Join, and help shape, the newly established Intelligent Modelling Lab for Weather, Climate and Water (iML-WKW).

How you contribute
As an MLOps Engineer, you ensure AI/ML models are production-ready, scalable, and reliable. You help translate research into operational value and contribute to systems that support early warning capabilities and broader societal impact. You will be part of the MLOps team responsible for designing, building, and maintaining a machine learning platform. You help bring models from research into operations and ensure they run reliably in production environments.

In this role, you focus on the operational side of the Research-to-Operations (R2O) cycle, building scalable infrastructure, automation, and monitoring.

We are expanding our newly formed MLOps team, and you will be part of establishing the team. You will design and optimize pipelines that enable machine learning models to be trained, tested, and deployed efficiently, while meeting the operational standards required for national decision-making systems.

The goal is to enable faster, more scalable, more reliable secure data-driven modeling infrastructure models for weather forecasting, water management, and climate adaptation. By combining advances in artificial intelligence, high-performance computing, and proven physics-based models, iML-WKW strengthens the Netherlands’ ability to anticipate and respond to extreme weather, water risks, and long-term climate change.

Your activities
You will work at the intersection of machine learning, DevOps, and data engineering. As part of a newly assembled team spanning Deltares, KNMI and Rijkswaterstaat, you will play a key role in shaping the infrastructure for machine learning pipelines. You bring developers, scientists and users together, align technical efforts, and help lay the foundation for a robust and reproducible ML environment. You will help researchers adopt reproducible, operational ways of working by shaping the guidelines, processes and practices that make the transition from research to operations faster, smoother and more reliable.

Your team
iML-WKW is a joint initiative between Deltares, KNMI, and Rijkswaterstaat. The focus of the team is on developing a robust, open, and future-proof digital infrastructure for next-generation models. You will be one of the 8 team members in this newly formed team within Deltares and KNMI. You will work in an agile framework with Matthijs (Deltares) as your Scrummaster and Joost (KNMI) as your product owner.

• bachelor’s degree in Computer Science,, or a related field and at least 2 years of relevant work experience in an agile environment
• 3+ years in MLOps, or 3+ years in data/software engineering
• experience with Python development and maintaining production-grade Python applications
• experience with software engineering best practices such as version control/git, CI/CD, automated testing, and dependency management
• experience building AI/ML pipelines and integrating ML libraries into production-grade systems
• experience designing and developing data-driven systems and scalable infrastructure
• experience working with machine learning libraries

Nice to have

• experience with cloud and/or on-premise environments
• experience with MLflow
• experience in a research-intensive or knowledge-driven environment

The MLOps team is a cooperation between Deltares, KNMI and Rijkswaterstaat. Deltares and KNMI are hiring multiple positions at each institute.

• The first selection interviews will take place in the week of 13th July at our KNMI office in De Bilt.
• Both KNMI and Deltares will conduct interviews in the same period.
• The job interviews will be done by a combination of people from KNMI and Deltares.
• By applying via Deltares, the employment arrangements for Deltares will apply. If you are interested to start in this team via Deltares please check their vacancy.
• CVs can be shared between institutes. If you apply for both, please let us know if you have preference.

General information

• Your official workplace is De Bilt.
• At the Royal Netherlands Meteorological Institute (KNMI), we actively encourage hybrid working. In consultation with your manager and colleagues, you can work from home or at the office, depending on the nature of your role.
• If we receive sufficient suitable applications, the vacancy may close earlier than the stated deadline.
• An (online) pre-selection test or assessment may be part of the recruitment process.
• Completing a case assignment and undergoing (online) screening, such as through databases, may also be included.
• Reference checks may be conducted as well.
• If you have questions about the application process, feel free to contact our Recruitment Advisor or visit our website for more information.

We do not respond to acquisition in response to this vacancy.