MLflow is an open-source platform designed to manage the machine learning lifecycle, including experiment tracking, model packaging, and deployment. It enables teams to log parameters, metrics, and artifacts during experiments, package models reproducibly with code and dependencies, and deploy models as REST APIs or batch inference jobs.