Use this skill to turn model work into a production ML system with clear data contracts, repeatable training, measurable quality gates, deployable artifacts, and operational monitoring. It helps plan or review production ML features, model refreshes, ranking systems, recommenders, classifiers, embedding workflows, and forecasting pipelines. Reach for it when you need to convert notebook code into a reusable training, evaluation, batch inference, or online inference pipeline.