Growing and Cultivating Strong Machine Learning Engineers

"I've been a little over 30 years in the software development area, in a variety of fields, done consulting, done software development, worked on products, worked with customers. Tried to do a variety of things over the years. The last a little over 12 years have been spent specifically on AI and machine learning, in a variety of contexts. I started at Nokia, working in that with maps and data analysis of users on their mobile devices."

"Then I moved to Microsoft. I've been here a little over 11 years, and 5 of those years I actually was a data scientist on the team, working with our AI platform team on figuring out what did people want to do with a cloud-based system, and helping customers onboard to it. Just generally see what was needed in order to scale up machine learning, and convince people that it was safe to be on the cloud."

Over 30 years of software development experience includes over 12 years focused on AI and machine learning across Nokia and Microsoft. Early work involved maps and user data analysis on mobile devices. Five years were spent as a data scientist working with an AI platform team to determine customer needs for cloud-based systems and to help onboard customers. Cloud adoption shifted significantly over the past decade from reluctance to widespread use. Seven years were spent managing AI teams, including machine learning engineers, applied scientists, product managers, and TPMs. Core topics include manager knowledge requirements, nourishing junior engineers, cultivating senior skills, and rotational program structures.

Read at InfoQ