MLOps Architect - AWS
9 days ago
Deep understanding of ML lifecycle: data ingestion, feature engineering, training, evaluation, model packaging, CI/CD, drift detection, monitoring, and governance. Experience implementing ML CI/CD pipelines including automated training, testing, validation, model promotion, and endpoint deployment.