Responsibilities
- Create, train, and refine machine learning models using Vertex AI components such as AutoML, custom training, and Vertex Pipelines.
- Construct scalable pipelines for feature processing, model training, evaluation, and deployment.
- Deploy trained models to production environments via Vertex AI endpoints and connect them to external applications or APIs.
- Work closely with data scientists, data engineers, and MLOps specialists to ensure consistent and dependable ML operations.
- Track model performance over time and implement alerting, retraining logic, and drift detection systems.
- Leverage Google Cloud services including BigQuery, Dataflow, Cloud Functions, Pub/Sub, and Google Cloud Storage in ML workflows.
- Apply continuous integration and continuous delivery practices to ML pipelines using Cloud Build and GitOps methods.
- Enforce model governance, version tracking, interpretability, and security standards within the Vertex AI environment.
- Maintain clear documentation of system designs, workflows, and model lifecycle stages for internal teams.
