This repository documents system design patterns for training, serving, and operating machine learning systems in production. It covers serving patterns including synchronous, asynchronous, batch, and microservice architectures, as well as caching and data handling patterns. The patterns are designed to be cloud and Kubernetes compatible, and largely language-agnostic. This serves as educational documentation for ML engineering teams building scalable production ML systems.