ML Systems Architecture & Components Questions

Design and architecture of production-grade machine learning systems, including data ingestion and preprocessing pipelines, feature stores, model training and validation pipelines, deployment and serving infrastructure, monitoring and observability, model governance, and platform-level concerns such as scalability, reliability, security, and integration with product systems.