Cloud Data Engineer; MLflow, english speaking

For a Swiss bank, a modern data platform is being built and operated. The platform integrates data from various source systems for analytics, enables exploratory analysis as well as the creation of reusable data products, and provides secure, granular access for business users (BI).

MLflow Setup & Integration :
Set up the tracking server, model registry, and artifact storage; integrate into on-prem environments and / or Azure Databricks (PoC); secure the setup in accordance with internal policies.

MLOps Enablement :
Establish CI / CD for ML models (e.g., Azure Dev Ops or Git Hub Actions); define workflows for training, validation, deployment, and monitoring; work closely with data scientists to achieve production readiness.

Documentation & Architecture :
Document setups, workflows, and best practices; help shape the target architecture and migration paths.

→ Hybrid (3 days / week on-site)

Solid hands-on experience with MLflow (on-prem and cloud), including Azure Databricks integration.

Experience with MLOps tooling (CI / CD, model lifecycle, monitoring).

Strong understanding of security, governance & compliance in ML workflows.

Fluent English (mandatory).