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The Organizational Impact Of An ML Engineer
Latest   Machine Learning

The Organizational Impact Of An ML Engineer

Last Updated on July 25, 2023 by Editorial Team

Author(s): Ori Cohen

Originally published on Towards AI.

The intricate relationship between DS teams, ML engineering & production independence


The World Of ML Engineering, Shinjuku, Tokyo, Dr. Ori Cohen.

These days the role of a Machine Learning Engineer (MLE) is becoming a necessity. Data science (DS) teams can’t operate independently and reach production without an MLE who practices MLOPs, i.e., without an MLE there is a good chance that DS teams will not be able to reach production.

There is a simple explanation for that. Everyone should yearn for data scientists to deliver production-ready products, and as fast as possible. The data scientist has less of an incentive to deep dive into the highly complex infrastructure world because their initial focus… Read the full blog for free on Medium.

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