Carter Bradley

It’s perhaps unsurprising that we’ve been receiving increasing numbers of questions about competing for advanced degree AI / ML talent. Upon starting to study the topic, what I found surprising was just how different this battlefield is from any other in university and early careers recruiting.

Here are a few reasons why:

First, and perhaps largest of all, the pool of candidates is small.

Very small. When members initially think about AI / ML talent, they typically think about PhDs (and maybe Masters) in Artificial Intelligence and Machine Learning. The pool of candidates from which companies are recruiting for these roles is slightly broader than that – with PhDs in Applied Mathematics, Applied Physics, and (some) computer science specialties coming in high demand. Nonetheless, what we are certain of is interest far outweighs the number of qualified candidates, especially since many of them pursue roles in academia… making an already small talent pool even smaller.

Second, recruiting processes can be long – and start very early.

Considering the importance – and value – of hiring an all-star, the high end of time investment has skyrocketed. We’ve seen an increasing number of employer-higher-education partnerships emerge – a new type of engagement where employers sponsor AI labs and fellowships or scholarships for PhD talent. I’ve even heard of companies engaging undergrads, high schoolers, and even middle schoolers who excel in math to start a relationship early. Some of these candidates wouldn’t even have the potential to start for a decade. Even when engaging a candidate towards the start of their PhD, companies can run 3-6 year processes.

Third, the compensation war is heating up. It is a simple supply and demand issue.

The demand for extraordinary AI / ML talent is high considering the value a single person can deliver. The supply is low. I won’t list specific amounts here, but even those paying top-of-market have consistently found themselves one-upped, sometimes by industries offering stocks, ghost equity, performance bonuses, and other additions to base compensation.

At the moment, the war for Advanced Degree AI / ML talent is narrow. Two dozen companies are doing this at scale, but there are hundreds more now interested in getting in the game.

In the next few years, I’d expect competition – and candidate volume – to rise substantially. And, for our part, we are beginning a significant investigation into this space. I’d welcome hearing from anyone on their strategies so far.