This tutorial aims to provide researchers with an introduction to the latest reproducible Machine Learning (ML) workflows and tools available through the NSF-funded Tapis v3 Application Programming Interface (API) and User Interface (UI). Through hands-on exercises, participants will gain experience in developing ML workflows and deploying them on Jetstream resources. We will emphasize the utilization of various Tapis core APIs, alongside specialized APIs such as Tapis Workflows and Tapis Pods, all seamlessly integrated within the user-friendly TapisUI. These production-grade services are designed to simplify the creation and facilitation of trustworthy, reproducible scientific workflows. By the end of this tutorial, researchers will be empowered to efficiently develop, deploy, and maintain their own ML workflows.