DevOps Engineer

You’ll join a platform engineering team supporting machine learning infrastructure for a major Belgian organisation. The team acts as the bridge between the core infrastructure function and data scientists, owning the multi-user Jupyter environment, MLflow, and Airflow that the data science community relies on day to day. This is a DevOps-leaning role rather than a data science one, so infrastructure fundamentals matter more than a data background., Lead and execute the migration from Bitbucket to GitHub, one of the team’s most time-sensitive priorities

Manage and evolve infrastructure as code using Terraform

Build, maintain and troubleshoot containerised workloads across Docker and Kubernetes

Support and improve CI/CD pipelines, including GitHub Actions

Maintain and optimise the multi-user Jupyter, MLflow and Airflow platform

Work across Linux-based environments to keep infrastructure stable and performant

Coordinate closely with infrastructure, data engineering, and data analytics teams to align on platform needs

Contribute to the ongoing evolution of the ML platform as usage and scale grow

Must-have: Python, Terraform, Kubernetes, Linux, hands-on containerisation experience (Docker)

Nice-to-have: GitHub Actions, MLflow, Airflow, prior Bitbucket-to-GitHub migration experience