AI job listings have become the fastest growing category on LinkedIn, and Indeed is packed with listings. But most job requisitions seek a computer scientist type with a PhD in neural networks or some other years-long study. The trick is to look past those, and you’ll find that what many companies need can’t be outsourced or given to a freshly minted college grad: an IT pro with enterprise-scale experience who also knows how to deliver on a machine learning project.
Machine learning is where the jobs are
Here’s the secret: There are plenty of AI-related jobs that aren’t advanced science but simply applying new machine learning features from cloud services giants to familiar IT environments. “Most ML jobs aren’t about advancing ML technology and algorithms,” says Ross Mead, founder and CEO of robotics software startup Semio and an industry consultant in AI with a PhD from the University of Southern California. “The money in AI for most companies is using ML for better business intelligence.”
That means using turnkey ML packages to analyze internal data—customer behavior, sales, etc.—to look for patterns that indicate likely business success. Machine learning is different from deep learning, the more esoteric field of AI that it is often confused with.
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