My Career Advice As a Google Researcher Working in AI for 20 Years Gaylord Contreras | usagoldmines.com

• Careers in AI are trending but the market is competitive for people with those skills.
• Google AI specialist Yann AïtBachir suggests building a strong foundation in technical skills.
• He also recommends starting in smaller companies before specializing in Big Tech.

This as-told-to essay is based on a conversation with Yann AïtBachir, an AI specialist at Google based in Singapore. This essay has been edited for length and clarity. Business Insider has verified his identity and employment.

Just under two months ago, I started working as an AI specialist at Google. That means that I’m helping companies build AI strategies and implement them using Google products.

Twenty years ago, only big military groups were hiring for AI. I worked mostly in startups and small companies early in my career. Most of my work at the time was about data analysis, data engineering, or data science.

With the AI boom of the last three or four years, the number of jobs and opportunities that are more AI-dedicated has increased a lot. Now many companies are investing into it and are transforming their operations and business using AI.

If I were to give advice to someone looking to build a career in AI, this is what I would say.

Come in with strong technical skills

While I studied AI 20 years ago, the fundamentals haven’t really changed. When you look at the system today compared to back then, the maps are the same, the statistics are the same, the probability is the same, and even the computer science system is the same.

You need to have very strong fundamentals in math, statistics, and computer science because all of the algorithms — even the recent ones — are built on the same core concepts.

AI is moving fast, and having a strong foundation helps you to pick up new changes faster because the concept behind the work is the same. That allows you to stay relevant.

While technical skills are important, they are not enough, especially as you grow in your career. No career is built in isolation. For you to be successful, you need to be able to collaborate with others.

Don’t jump immediately into Big Tech

If you want to grow a career in AI now, it’s about how you’ll be different. You need to specialize in one area of AI because it’s quite a wide scope with generative AI, predictive AI, and natural language. Now, if you want to be successful, you need to be more specialized.

There are many different roles that you can do. You can be an engineer, you can be a researcher, you can work on product management, or you can have a role that is more consumer-facing. So I advise everyone, especially early in their career, to start being an explorer. Try different things, experiment, and discover really what excites you and interests you.

I recommend not jumping immediately into Big Tech early in your career. The reason for that is because a career is very long. It’s not really a sprint, it’s a marathon. You might not know exactly what you like to do and you might change as you are getting older.

I think that you have much more opportunity to grow and to discover when you work in a smaller company. You will be exposed to a much wider scope of work. After, if you really want to specialize in one area, a Big Tech company can help you narrow your scope and go even deeper in some areas.