MLOps Engineer

Do you want to work at the forefront of next generation weather forecasting? At the KNMI, you contribute directly to high quality and reliable weather predictions and impact models that are essential for a safe and livable society. Rapid developments in artificial intelligence and machine learning (AI/ML) are fundamentally changing how weather forecasts are created. The KNMI is internationally leading in AI/ML research and is now moving these innovations into operational use. To accelerate this transition, we are looking for an MLOps engineer who will help bring research into production and further develop a scalable machine learning platform. Want to build technology that truly makes an impact? Apply now.

How you contribute
You ensure that AI/ML models are production ready, scalable and reliable. You help translate research into operational value and contribute to the development of systems that support early warning capabilities and societal impact. As an MLOps engineer, you will be part of the MLOps team responsible for designing, building and maintaining the machine learning platform of the KNMI. You play a key role in bringing models from research to operations and ensuring they run reliably in production environments. Within this role, you focus on the operational side of the R2O cycle and work on scalable infrastructure, automation and monitoring.

Your activities

• design, build and maintain end to end AI/ML pipelines from data ingestion and training to deployment and monitoring
• bring AI/ML models from advanced research stages into operational environments
• build and maintain CI/CD pipelines for AI/ML workflows
• design and improve infrastructure for scalable and reliable model execution
• implement monitoring, logging and validation for model performance and reproducibility
• collaborate closely with AI/ML researchers, engineers, data scientists and stakeholders across product chains
• contribute to improving ways of working, automation and platform maturity

Your team
You will join the MLOps team within the department R&D Observations and Data Technology department. The team focuses on building a reliable and scalable platform for training and inference of complex machine learning models. You will work in a multidisciplinary environment with software engineers, data specialists, AI/ML scientists and domain experts. The department consists of around 40 professionals working in agile teams with a strong DevOps mindset. The working environment is Linux based, with a strong preference for open source and open standards. The team is international and diverse. English is the primary working language.

• bachelor degree in computer science, data science or similar
• 2+ years experience in MLOps or 3+ years in data/backend engineering
• experience developing and maintaining production-grade Python applications
• experience with software engineering practices such as version control, CI/CD, automated testing and dependency management
• experience with building AI/ML pipelines and integrating ML libraries into operational/production-grade products
• experience with designing and developing data driven systems

Nice to have:

• experience working in agile teams
• experience with cloud environments, preferably AWS
• experience with CI/CD, CloudFormation, MLflow
• experience in a knowledge intensive or research environment
• experience with stakeholder management

• The selection interviews will take place at our KNMI office in De Bilt.
• 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.