ML engineering can be defined as the technical systems and processes associated with the stages of the ML lifecycle (also referred to as MLOps cycle) from data preparation, modeling building, and production deployment and management. While ML engineering entails the provisioning, deployment, and management of infrastructure that enables model building, data labeling, and model inference, it can go much deeper than that ...