DevOps Engineer
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- fixed term Start Date: 1st September
About the Role
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.
Key Responsibilities
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 Required Skills Must-have: Python, Terraform, Kubernetes, Linux, hands-on containerisation experience (Docker) Nice-to-have: GitHub Actions, MLflow, Airflow, prior Bitbucket-to-GitHub migration experience Interview Process Fast-moving process. Start date can land the week after final interviews.
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