Chapter 2. People of MLOps
Even though machine learning models are primarily built by data scientists, it’s a misconception that only data scientists can benefit from robust MLOps processes and systems. In fact, MLOps is an essential piece of enterprise AI strategy and affects everyone working on, or benefiting from, the machine learning model life cycle.
This chapter covers the roles each of these people plays in the machine learning life cycle, who they should ideally be connected and working together with under a top-notch MLOps program to achieve the best possible results from machine learning efforts, and what MLOps requirements they may have.
It’s important to note that this field is constantly evolving, bringing with it many new job titles that may not be listed here and presenting new challenges (or overlaps) in MLOps responsibilities.
Before we dive into the details, let’s look at the following table, which provides an overview:
|Role||Role in machine learning model life cycle||MLOps requirements|
|Subject matter experts||