MLOps-engineer voor uniek team!

# MLOps Engineer at Deltares and KNMI

Are you ready to leverage your Machine Learning Operations expertise to optimise the potential of ML models and bring them from research to practice? Join the recently established Intelligent Modelling Lab for Weather, Climate and Water (iML-WKW).

## Responsibilities

You will work at the intersection of machine learning, DevOps and data engineering. As part of a newly assembled team with members from Deltares, the KNMI and Rijkswaterstaat, you will play a key role in shaping the infrastructure for machine learning pipelines. You bring together developers, scientists and users, align technical efforts and help establish the foundation for a robust and reproducible ML environment.

You will support researchers in applying reproducible, operational practices by developing guidelines, processes and methodologies. You work in an agile environment with a Scrum Master and product owner.

You focus on the operational side of the Research-to-Operations (R2O) cycle, setting up scalable infrastructure, automation and monitoring.

## Requirements

• 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 of experience in MLOps, or 3 years in data engineering or software engineering
• Experience with Python development and maintaining Python applications in production environments
• 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-ready systems
• Experience designing and developing data-driven systems
• Experience working with machine learning libraries

## Desirable

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