MLOps-engineer voor uniek team!

# MLOps Engineer at Deltares and KNMI

## About the role
You will join the recently established Intelligent Modelling Lab for Weather, Climate and Water (iML-WKW), a joint initiative of Deltares, KNMI and Rijkswaterstaat. You will be one of eight team members in this newly formed team.

## Your responsibilities
You will work at the intersection of machine learning, DevOps and data engineering. As part of the team, you will play a key role in shaping the infrastructure for machine learning pipelines. You bring together developers, scientists and users, coordinate technical efforts and help lay the foundation for a robust and reproducible ML environment.

You will help researchers adopt reproducible, operational practices by shaping guidelines, processes and methodologies that improve the transition from research to operations. You will work in an agile environment with a Scrum Master and product owner.

## Your impact
As an MLOps Engineer, you ensure that AI/ML models are production-ready, scalable and reliable. You help translate research into operational value and contribute to systems that enable early warning capabilities and broader societal impact. 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 related field and minimum 2 years of relevant work experience in an agile environment
• 3+ years of experience in MLOps, or 3 years in data or software engineering
• Experience with Python development and maintaining Python applications for production environments
• Experience with software engineering best practices (version control/Git, CI/CD, automated testing, dependency management)
• Experience building AI/ML pipelines and integrating ML libraries into production-ready systems
• Experience designing and developing data-driven systems
• Experience with machine learning libraries

## Plus

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

## Benefits

• Inspiring environment that stimulates innovation and professional development
• 12-month contract (minimum 32 hours) with intention to convert to permanent contract
• 34 vacation days based on a 40-hour work week
• ABP pension, mobility budget and healthcare expense reimbursement
• Flexible work environment with work-life balance