End-to-End ML System Design Questions

End-to-end design of machine learning systems, covering data collection and validation, feature engineering and feature stores, model training and evaluation, deployment and serving architectures, monitoring and incident management, retraining pipelines, data governance, scalability, security, and MLOps practices.