Your MLOps team
You just learned about the potential roles that are involved in MLOps processes. Even though the precise names of roles can differ for different projects or companies, there are core responsibilities to each role that are required in every project. Having clearly defined roles allows every role to focus on its own set of responsibilities which streamlines MLOps processes.
Imagine you are a data scientist, and you work in a team where you are training a machine learning model to use in your business. You have hired someone to collect, process, and store data for you, but you need someone to deploy the model once it is finished. For which role should you create a vacancy?
This exercise is part of the course
MLOps Concepts
Hands-on interactive exercise
Turn theory into action with one of our interactive exercises
