About the role

You will join a team responsible for building and scaling the ML platform used by 300+ data scientists and ML engineers across 60+ teams. Your work will directly impact how machine learning models are deployed to production — reliably, securely, and at scale.

You’ll spend most of your time implementing and standardising Databricks MLOps (environments, CI/CD pipelines, model monitoring) while also contributing to the evolution of a battle‑tested AWS SageMaker platform.

You day-to-day:

• Design, build, and scale a production-grade ML / MLOps platform
• Implement Databricks MLOps (environments, CI/CD pipelines, monitoring)
• Maintain and improve the AWS SageMaker ML platform
• Automate infrastructure and workflows using Python and Infras...