You now have a framework for ML system design interviews. You can structure answers across requirements, data, model, serving, and evaluation.
You've practiced common design problems: recommendations, fraud detection, content moderation, and search ranking. You understand feature stores, serving patterns, and monitoring.
Next, you'll learn MLOps for production ML.