I started hearing the job role of “machine learning engineer” a few years ago. In mid 2017 we wrote a post describing the role that we were observing in a few companies mainly in the technology sector. At the time, companies were carving out a new role focused on making machine learning and data science work in production. Today, machine learning engineer has become a much more established job title. The chart below displays the count of the number of job postings that mention “data engineer” or “machine learning engineer” respectively:
Overall across the metro areas we examined, the number of job postings that mentioned “machine learning engineer” was about one fifth (20%) the number of job postings that mentioned “data engineer”. But in the SF Bay Area, the number of job postings that mentioned “machine learning engineer” was close to half of those that mentioned “data engineer” (47%):
To the extent that the SF Bay Area is an early adopter of technology and technology practices, look for the job title “machine learning engineer” to become mainstream in other locations. We are still in the early stages of enterprise adoption of machine learning. One sign that companies are taking ML much more seriously is the emergence of yet another term (and job role) in the SF Bay Area: MLOps. So far there are very few job postings that contain this term (MLOps). But if my professional network is any indication, I believe this will change in the years ahead.
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