Set up SageMaker Unified Studio platform domain configuration, project provisioning, persona-based roles, and multi-environment (Dev, Prod-UAT, Prod) promotion workflows
Build MLOps pipelines using SageMaker Pipelines data extraction from Snowflake, preprocessing, training, evaluation, and model registration
Manage SageMaker Model Registry cross-account model promotion, versioning, immutability, and lineage tracking
Configure MLflow experiment tracking auto-logging of parameters, metrics, and artifacts
Set up identity and access management Okta SSO, SailPoint entitlements, persona-based execution roles, service roles for pipelines
Build model serving real-time SageMaker endpoints and batch prediction workflows
Set up model monitoring data drift, model drift, performance degradation detection
Configure data catalog searchable datasets, access-level visibility, access-request workflows, lineage