How Startups Are Grappling With the Artificial Intelligence Talent Hiring Frenzy
With A.I. experts commanding salaries of around $300,000, it’s a challenge for startups to woo this rare talent.
PHOTO CREDIT: Getty Images
When Devaki Raj, the founder of the Mountain View-based deep learning startup CrowdAI, and Inc. 30 under 30 alum, learned that an artificial intelligence engineer she was trying to recruit was in the hospital, she didn't think twice about what she did next: Raj showed up at the hospital with flowers and balloons. She wanted to make sure the candidate got the message that her startup would be a very different atmosphere than what he'd get at a larger company.
There's a talent war brewing between startups and big companies as both scramble to find top-notch artificial intelligence experts in a relatively small labor pool.
"There's just not enough talent out there," Raj says.
The number of experts in this field is not clear--Montreal startup Element A.I., which helps businesses build machine learning teams, estimates that there are some 20,000 PhD-level computer scientists around the world capable of building A.I. systems. These are the experts who are needed to develop autonomous cars, facial recognition technology, virtual assistants, and more. What is clear is that tech giants are trying to lure them by offering exorbitant salaries that can start at $300,000 a year, according to Bloomberg.
The struggle to find A.I. talent is hard felt for startups that can't throw around cash as easily as companies like Google, Amazon, or Facebook. According to a McKinsey report, tech giants invested $20 billion to $30 billion in A.I. in 2016. Startups that need to staff up in A.I. face the additional hurdle of finding talent that is unique enough to solve the specific challenge that they're working on.
With A.I. still a relatively new field, tech companies often look to recruit experts from universities who are working on the cutting-edge of the technology and steeped in high-level mathematics and statistics. For instance, in 2015, Uber hired 40 people from Carnegie Mellon to work on its self-driving car project. But such recruits don't always transfer so neatly in a startup environment.
CrowdAI maps out infrastructure changes such as roads and buildings on a global scale, and counts among its clients Udacity, Planet Labs, and Cruise Automation. Because the startup collects data on satellite and aerial imagery, particularly in areas not well-mapped in the world, CrowdAI works with a lot of messy data, which may be an unfamiliar challenge for experts in academia. Raj says she wades through hundreds of resumes in a week and often notices that applicants will have the deep learning background needed but not necessarily the startup experience to "actually implement these things in a clear structure."
"At a startup everything is fairly ad hoc--you have to be able to work with certain types of uncertainty," she says. Raj added that she's essentially "looking for a unicorn" who has the academic experience but also capabilities of working production-ready work.
The other problem startups face is seeing their recruits snatched up before they even have time to make an offer. Once candidates learn of higher salaries elsewhere, they often don't wait around for an offer, says Sameer Maskey, founder of New York-based FuseMachines. He's experienced that scenario more than once. Founded in 2013, his startup develops automated sales and customer service platforms. "Many candidates have gone just because we could not afford it," he says. (His offering salary starts at $120,000.)
So the founder started looking elsewhere. Maskey, who is also a machine learning professor at Columbia University, said that he started sourcing from around the world to address the talent shortage. After four-and-a-half years, he built a team of almost 100 remote A.I. engineers from Nepal, Canada, and the Dominican Republic. Maskey says he realized that there is a lot of undiscovered talent in developing countries--they just might not have spent 10 or so years earning a PhD degree.
Seeing that the model worked for his team, Maskey created a fellowship program within his startup last year that sources and trains remote A.I. engineers for other companies in need of this talent.
Companies outside of technology, telecom, and finance face even bigger hurdles when trying to recruit A.I. engineers. The expertise hasn't really trickled down to other industries yet, according to the McKinsey report.
"In the medical field, you wouldn't even be able to recruit someone with medical device experience and A.I. experience. That would be a true unicorn because A.I. hasn't been applied to that area," says Peter Verrillo, founder of Enhatch, a New Jersey-based medical device technology company that builds planning and logistics software for surgeons to plan in advance of the procedure. His team is 20 employees, eight of which are dedicated to working on A.I., and Verrillo is looking to hire more A.I. engineers in the future.
When he does, he might want to bring balloons and flowers--the engineer CrowdAI's Raj wooed in the hospital joined her team in February.