DevOps Engineer
Type: Freelance / (Statement of Work)
Duration: 6 months - 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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