Machine Learning Engineer – AI Implementation & MLOps

Our client, a dynamic organization in the public services sector, is seeking a specialist to drive the operationalization of machine learning solutions. The role focuses on building robust implementation, monitoring, and scalable ML pipelines within both cloud and on-premise environments.

• Design, build, and maintain production-ready machine learning models and end-to-end ML pipelines.
• Process and analyze data from diverse sources to implement feature engineering and ensure data quality.
• Translate experimental models into scalable services by integrating them into backend APIs and batch processes.
• Establish MLOps practices, including CI/CD processes, version control, and model registry management.
• Monitor model performance, latency, and drift to ensure long-term stability and reliability.
• Collaborate with cross-functional teams to align technical implementations with the European AI Act.

• 3+ years of experience in data and machine learning development using Python.
• 1+ years of experience with Machine Learning libraries such as scikit-learn, PyTorch, Langraph, Ollama, and LangChain.
• 1+ years of experience with MLOps practices, including Azure DevOps, CI/CD, and experiment tracking.
• 1+ years of experience with containerization using Docker and deployment patterns.
• 1+ years of experience in SQL and data processing within production environments.
• 1+ years of experience with backend development using C#, .NET, and Blazor.
• Experience with monitoring tools such as DynaTrace, OpenTelemetry, and drift detection.
• Strong analytical skills and a proactive, ownership-oriented mindset.
• You are fluent in Dutch or French with a passive knowledge of the other language.

Nice to Haves

• Practical knowledge of Azure cloud infrastructure.

• Start date: ASAP
• Duration: project length
• Work regime: Full-time
• Location: Brussels
• Working model: Hybrid (2 days onsite per week)
• Contract: open to both permanent employees and freelancers