The role

Reporting to the Head of Data Engineering, Reporting and Governance, this role is a key member of the team responsible for managing and enhancing one of our new advanced ML engines, helping to deliver real value through the continuous improvement of this new strategic asset.

Roles & Responsibilities

End-to-end ownership of a bespoke ML engine hosted in Databricks.
Design, build and evolve architecture for model execution, retraining, monitoring and config layers.
Deploy, tune and manage models
Own CI/CD, rollback, monitoring and production stability.
Build and maintain pipelines for ingestion external datasets - handling data anomalies, latency and interdependencies.
Enable flexible updates in response to commercial drivers.
Own config tooling, override logic and change-release pathways.
Develop deep understanding of relevant commercial mechanisms and how the ML engine logic interacts with them.
Co-own system performance with subject matter experts and analysts.
Act as the link between engine behaviour and commercial outcomes.
Own Unity Catalog security (RBAC, PII, secrets, audit/audience access reviews).
Databricks Unity Catalog, Delta Lake, MLflow (registry & stages), Workflows.
Observability on ML models: Set up key metrics, and alerts for latency, success rate, cost, and model output drift.
Drive FinOps: budgets/alerts, cost attribution and performance tuning, ensuring costs are kept within defined budget.

AI Jobs in Richmond Vic

Machine Learning /Data Engineer