Cade Metz (@CadeMetz) recently wrote about Artificial Intelligence (AI) salaries and the scarcity of AI talent in the New York Times.
Tech Giants Are Paying Huge Salaries for Scarce A.I. Talent
Here is what I think.
Artificial Intelligence (AI) is one of the hottest field in technology today. Companies use AI to automate tasks typically done by people, and major technology firms see it as the groundwork for their next generation of intelligent products.
On Budgets
Tech’s biggest companies are placing huge bets on artificial intelligence, banking on things ranging from face-scanning smartphones and conversational coffee-table gadgets to computerized health care and autonomous vehicles.
Who are the biggest players in this race for talent? Glassdoor searched millions of U.S. job listings for job titles with the words “artificial intelligence,” “AI,” or “deep learning.” They found 512 such roles. According to Glassdoor, the top 15 employers who are seeking AI expertise are: Amazon, Nvidia, Microsoft, IBM, Accenture, Facebook, Intel, Samsung, Lenovo, Adobe, MoTek Technologies, Uber, Accenture, Rakuten Marketing, and Wells Fargo. (Forbes, 2017)
Nearly all big tech companies have an artificial intelligence project, and they are willing to pay experts millions of dollars to help get it done.
Companies dedicate large R&D budgets, which includes investing into various artificial intelligence technologies. Every quarter, Amazon spends $5.9 Billion USD ($4.4 Billion GBP), Alphabet $4.2 Billion USD ($3.1 Billion GBP), Microsoft $3.6 Billion USD ($2.7 Billion GBP), Facebook $2.0 Billion USD ($1.5 Billion GBP). (YCharts, 2017)
On Salaries
Typical A.I. specialists, including both Ph.D.s fresh out of school and people with less education and just a few years of experience, can be paid from $300,000 to $500,000 USD ($222,000 to $369,000 GBP) a year or more in salary and company stock, according to nine people who work for major tech companies or have entertained job offers from them.
In United States, Artificial Intelligence Engineers make $143,000 USD ($106,000 GBP) per year, while Machine Learning Engineers make from $121,000 USD to $166,000 USD ($89,000 to $123,000 GBP) per year, while Data Scientists make $129,000 USD ($95,000 GBP) per year. (Paysa, 2017; Cyber Coders, 2017; Paysa, 2017)
On Demand
What about the rise of demand? According to IT Jobs Watch, who source data from IT recruitment services, the demand for Machine Learning Engineers increased by 290% from 2015 to 2016, by 208% from 2016 to 2017. (IT Jobs Watch, 2017)
Giant tech companies like Facebook and Google also have plenty of money to throw around and problems that they think A.I. can help solve, like building digital assistants for smartphones and home gadgets and spotting offensive content.
On Shortage
Many think the talent shortage won’t be alleviated for years. “Of course demand outweighs supply. And things are not getting better any time soon,” Yoshua Bengio, a professor at the University of Montreal and a prominent A.I. researcher, said.
There is a staggering talent shortage in the world for artificial intelligence talent. Fewer than 10,000 people in the world have the skill set to conduct AI research, according to technology and consulting firm Element AI. (Forbes, 2017)
So where is the talent accumulating? According to Glassdoor, nearly 50% of employees seeking AI talent are based in Silicon Valley. (Forbes, 2017)
On Investments
Amazon is the the most hungry artificial intelligence recruiter. They are investing $228 Million USD (or $169 Million GBP) annually into AI projects and they currently have 1,178 AI jobs posted. (Forbes, 2017)
I think it’s important to look outside the big tech companies to see how investment dollars are being invested. Consider that there are more than 1,965 Artificial Intelligence companies across 70 countries who have raised more than $23.7 Billion USD ($17.5 Billion GBP) in funding. (Venture Scanner Insights, 2017)
How much money should you be investing into AI and machine learning? According to a recent report, companies are expected to spend more than 15% of their budgets towards machine learning. (Statistica, 2017)
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