MLOps setup — model registry, serving and monitoring

Project Description

We have four models in production, all deployed differently, none monitored. Two were trained by someone who has left and we cannot reproduce them. We want a standard path: experiment tracking, a model registry, containerised serving, and drift and performance monitoring that alerts. Retraining should be a documented pipeline, not an afternoon of someone's memory. This is platform work rather than modelling. Please send infrastructure you have built, not notebooks.

Skills Required