Readying Your Company For A Machine Learning Talent Pipeline

For a very long time, we’ve heard about shortages of people with specific skills but most of those skills in question tend to be on the newer side of the spectrum. For example, if you listen to people at Google and Amazon, they’re in dire need for machine learning talent. Unfortunately, that represents a small percentage of people in the field. There are just so many PhD’s with an education in machine learning over the last three years. Considering that most of the practical machine learning advances happened in the previous five years, this defines an incredibly small number of people.

Meanwhile, we’re approaching a situation where more companies are dipping their toes in the water and finally making an effort to develop skill sets for their people in machine learning. There’s a terrific course by Andrew Ng on Coursera that is a non-technical description of machine learning from the business point of view where he discusses where things are in machine learning today and what companies interested in developing machine learning talent should foresee.

Ng is telling companies that, if they’re genuinely committed to it, it’s going to take two to three years to develop their Machine Learning (ML) teams and achieve some, initially small, project wins to demonstrate to the rest of the organization what ML can do for their firm.

Now, we’ve been talking about this influx of machine learning talent for several years – longer than expected, in fact. That said, we should expect a fair number of companies in a variety of industries finally begin to move toward building AI machine learning teams and starting machine learning projects.

They’re already realizing that for every machine learning expert, they need a lot of software expertise that coincides with a number of them looking to get much more aggressive about building things in the cloud.

The Cloud And Machine Learning Talent “Bottleneck”

Everybody is trying to get through the door at the same time, which creates a bit of a problem. While you have a fair number of colleges trying to educate people on newer technologies such as the cloud and ML, change doesn’t happen overnight. The more aggressive coding camps are helping, but these are challenges that will take a while to resolve.

In the meantime, we are in the early stages where many companies don’t exactly know what they need to do to succeed on the ML front. They do know that building an AI team is a start as they can’t ignore the significant technological shift and a greater maturity of the field, with more tools that are easier to use.

From a hiring perspective, as companies better appreciate what needs to be accomplished on each project, they will come to realize that perhaps they don’t absolutely need to hire someone with a PhD from Carnegie Mellon or someone working with a division of Google. After all, if that’s the only person who can solve your problem, you may have a very tough time getting them into your environment. But there’s some good news.

Talman Advantage #3: The Preparation For The Interview You Deserve

You can’t go into an interview armed with only a resume to represent you. Roy Talman & Associates gets you ready for the experience with a far more in-depth level of preparation, including an evaluation of your skills in light of what today’s marketplace demands.

Through testing on certain subjects and measuring your scores against what our clients expect, you’ll be able to head into the interview knowing so much more. You’ve come too far to settle for anything less. So make sure you talk to Talman first.

The Pool May Be Expanding

One of my favorite authors, Ray Kurzweil, recently mentioned in a speech that the amount of computing dedicated to machine learning has been doubling every quarter. If that trend continues, we’re going to begin seeing it everywhere very, very quickly. And with the expansion of talent dedicated to this area of learning, the good news is that you probably won’t need to compete for precisely the same people that Google is snapping up the minute they get PhD’s. That’s where things will get really interesting.

As this technology grows to permeate more of our economic lives, companies will need to invest in machine learning and take advantage of exponentially more useful machine learning tools within the next couple of years or they may be seriously left behind. Case in point: I was listening to an interview with Masayoshi Son, the CEO of SoftBank Group and a manager of $100 Billion Vision Fund, where he said he is “all in” on machine learning in all forms. He has invested billions of dollars in machine learning because he believes it is going to be used everywhere and used for almost everything, from chip companies to autonomous car driving.

What Represents A Good Start For Your Company?

Turning first and foremost to a recruiter with a long-established foothold in technical areas such as Roy Talman & Associates can help, especially as we have a finger on the pulse of what’s new and next. We’re currently in discussion with a number of companies who have approached us for help in developing a presence in ML. Typically this comes about because an individual who has known us for a number of years is now a true expert in ML, with the capability to build something substantial.

Some of these individuals aren’t necessarily trying to be presented at various companies and receive offers, but they are looking for counsel for when the right opportunities and applications for their skill set come along.

That’s a case of being in the right place at the right time for candidates and companies alike. With the soon-to-be proliferation of machine learning expertise in many fields, don’t muddle along with the status quo for too long. Make the right move and Talk To Talman First. Because this is one trend we expect to not only impact our business but quite possibly your own as well.