Top 3 Traits To Look For When Hiring AI/ML Talent

Before hiring AI talent in your company, ask yourself, “What are the main traits that characterize the ideal hire?”

Based on their particular project or use case, most hiring managers focus on ‘years of experience’ and formal education. For example, it’s common to see AI job descriptions requiring 10+ years of experience and a PhD.

First of all, has practical artificial intelligence even existed for anywhere near 10 years? (And even if it did, with technology changing so rapidly, how much of that ‘experience’ has long become obsolete?) Does a PhD even remotely hint to practical applications of AI? Don’t get me wrong – experience and formal education are helpful, but they are not the most important factors that make AI engineers successful.

Here are the top 3 traits to look for when hiring AI talent today:

1) Resourcefulness

In my experience, resourcefulness is perhaps the most important and powerful trait exhibited by machine learning engineers.

Since no company or use case is identical to another, it is inevitable that your team will come across a problem that is, to an extent, unique to your company. You could be using custom data that is specific to your company and use it to train a custom model. If the model yields unexpected or strange behavior, what is going on? Often, the ‘debugging’ process for machine learning systems is not trivial. AI systems often seem to ‘work well’, yet fail silently behind the scenes.

Having strong machine learning engineers and data scientists in your team who are able to solve a problem quickly, even if they have never encountered it before, is priceless. This trait is a combination of two factors: strong belief they will find the solution, and meticulous attention to detail as they explore the problem from multiple perspectives.

During interviews, ask candidates about a time when they hit a wall working on a machine learning problem and how they were able to break through. Listen to their thought process about how they arrived at the solution.

2) Strong AI and Machine Learning Fundamentals

As mentioned previously, years of experience and formal education do not translate to success on the job. This fact has been proven by Google, Amazon, Facebook, Apple, Netflix, Airbnb, and many other companies.

From working with clients and learning from other AI/ML teams, one of the most important traits exhibited by high-performing machine learning engineers is a strong understanding of the fundamentals.

The specific technical AI concepts are beyond the scope of this article, but make sure you screen for this during job interviews. You definitely need a minimum of 1 strong AI engineer or AI consultant to help you ask these questions and assess candidates from a technical perspective.

Technical interviews in AI/ML are different than technical interviews for software engineering roles. Python coding challenges are fine, but machine learning fundamentals are more important. Check out my other blog post titled, “AI/ML Job Interview Tips for good AI technical questions to ask.

3) Passion for Continuous Learning

Given that the field of artificial intelligence is changing so rapidly, it is more important than ever that machine learning engineers and data scientists in your team stay on top of latest practical developments and technologies. Passion for continuous learning is no longer a luxury, but a must-have for technical members of your AI team.

How do you assess this trait during the interview process? Simple.

One way is to see their education trajectory AFTER college/university. Unfortunately, most people stop learning by choice as soon as they graduate from a formal educational institution. Lack of self-education is a red flag, and you want to avoid those candidates (unless you are hiring interns).

However, if you see that a candidate has been learning and developing his/her skills consistently for the past 6-12+ months, that is a great indicator of someone with high chances of success on the job. For example, they may have taken multiple online AI courses, attended AI seminars/workshops, etc.

Bonus: If a candidate has been going a step further and TEACHING what they learn, it almost invariably means this is a strong candidate with the highest chances of success. He/she may have a technical YouTube channel, blog, podcast, Meetup, or online group teaching the latest technical concepts. This bonus candidate can also coach and train other members of your AI team and help them improve their skills. These are some of the best people to have in your team, and they do wonders for your AI culture.

There are other important traits to consider when hiring AI engineers, but these are some of the most important ones.

If you need help to accelerate your company’s machine learning efforts, or if you need help getting started with enterprise AI adoption, send me a LinkedIn message or email me at info@carloslaraai.com and I will be happy to help you.

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