The MLOps engineer role is different from an ML engineer role. Even though the role varies from company to company, in general, ML engineers focus more on bringing individual projects to production, while MLOps engineers work more on building a platform that is used by machine learning engineers and data scientists.
"ML engineers focus more on bringing individual projects to production, while MLOps engineers work more on building a platform that is used by machine learning engineers and data scientists"
This should be in a large org, because I commonly find those roles are essentially the same
This is very well-thoroughly written. I wish we had university courses based on this. Most universities do not update their course syllabus.
This is great I would love to see a visual of this in a supply chain type of motion showing left to right flow.
Great resource
Thank you for such a valuable article.
for MLOps principles, I think we can add this one https://ml-ops.org/content/mlops-principles
Thanks for the list, super great
"ML engineers focus more on bringing individual projects to production, while MLOps engineers work more on building a platform that is used by machine learning engineers and data scientists"
This should be in a large org, because I commonly find those roles are essentially the same
Wow it’s a detailed roadmap
I will take it as my new year resolution to complete the learning and build a project