In today’s scorching hot labor market, securing top-tier tech talent has never been more difficult or more important. When it comes to capturing just how fierce the competition is, Susan Dominus of the New York Times Magazine puts it best: “Along with microchips, toilet paper, and COVID tests, tech workers will be recalled as one of the great, pressing shortages of this pandemic. Estimates of the unemployment rates for tech workers are about 1.7 percent, compared with roughly 4 percent in the general economy; for those with expertise in cybersecurity, it’s more like 0.2 percent.”
These numbers are staggering, even for an industry with a history of going to extraordinary lengths to recruit professionals with expertise in new, cutting-edge fields. However, the competition is justified when it comes to the race for AI/ML talent.
Artificial intelligence and machine learning are already transforming industries, automating complex tasks, and processing massive amounts of data in ways we couldn’t have imagined just a few years ago. Companies that leverage AI and ML effectively will quite literally be smarter than their peers and enjoy a competitive edge for years to come. The challenge for companies now is doing the legwork necessary to attract engineers who can pave the way to this exciting new reality.
Recruiting AI/ML professionals is exceptionally difficult because finding engineers with the diverse skill sets necessary to succeed in this field is akin to finding a needle in a haystack. Historically, some folks studied advanced math and data science while others focused on developing their software engineering chops. AI/ML, however, lies at the intersection of pure data science and software engineering. To excel in the field, professionals need to transition seamlessly from, say, working in a Jupyter Notebook to deploying advanced production systems. Because the field is so new and the job requirements so challenging, many tech companies struggle to find professionals with the depth and breadth necessary to excel in AI/ML.
Although the race for tech talent is fierce, it is not unprecedented. In the tech industry’s initial boom in the mid-2000s, companies went all out to attract coders, offering huge salaries and building palatial offices decked out with ping pong tables and in-house dry cleaners. As the tech industry has matured, however, recruiting has evolved. While lavish offices and unlimited snacks once ruled the day, today’s tech workforce now has a newfound appreciation for work-life balance, the benefits of flexible work-from-home policies, and the opportunity to impact the world positively. Ultimately, in my experience, prospective employees want nothing less than to be part of a team that helps make the transformative promise of artificial intelligence and machine learning a reality. This requires employers to throw out their old recruitment playbooks filled with platitudes and be more reflective and transparent with their would-be employees than ever before.
While recruiting can feel impossible at times, it can be done. Over the past year, Prove, a leader in digital identity, has more than doubled its headcount to just under 300 employees, many of whom are industry thought leaders and experts in the AI/ML space. Follow this playbook, and you too will be able to grow your team.
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