Writer Sun Ran, Yang Lin
Editor’s note:
Many believe AI-powered automation is likely to replace human workers and spell an end to the human race.
Before resulting in unemployment in large scale or bringing about a catastrophe, development in AI and the competition in the AI industry have brought AI engineers abundant job opportunities and decent salaries.
From big tech names to early-stage startups, companies need to chase after AI talent if they want to make the most out of this technological innovation, regardless of the cost.
This is the Part 3 out of the total three.
Going “shopping” in Silicon Valley
As it becomes exceedingly hard for companies to land AI specialists from the tiny talent pool in China, some companies, mostly startups that have closed series B financing round with a valuation over hundreds of millions of dollars, have went “shopping” abroad.
In the last six months alone, TalentSeer, a talent sourcing company founded by Alex Ren, has been showered with 200 AI talent requests from a dozen AI companies.
How much does it cost to round up an AI team in Silicon Valley? According to Alex, an AI team follows the structure of a pyramid.
The unique talent at the top is usually a PhD with at least a director title in those tech titans or a professor/associate professor. The roles (usually one to two) further down the slope are filled by PhDs with five years’ work experience or master graduates with seven to eight years’ work experience, preferably technical managers.
The positions at the bottom are for freshly graduated PhDs and master graduates. It takes 10 to 20 members to form a typical AI team.
To snap up AI talents, companies often have to dish out big money. Currently, the minimum annual salary offer for an AI scientist with two to three years’ work experience is $150,000. If it is in Google or Facebook, he or she can enjoy an extra $50,000 to $100,000 stock benefits, bringing the total annual salary to $200,000. Don’t forget that we haven’t even factored in other benefits like healthcare yet.
Not all companies can afford to recruit AI specialists abroad. But, the demand in China has far outstripped the supply, which leaves the companies no choice but to do some mining in Silicon Valley.
The chances of them luring AI specialists to China are slim, but the startups are willing to take their shots.
For Alex, it’s nothing unusual to bump into CEOs of Chinese AI startups in the coffeehouse near Stanford University. “They travel to Silicon Valley very often to scour for AI talents,” said Alex.
At this year’s National People’s Congress and the National Committee of the Chinese People’s Political Consultative Conference, Robin Li, founder of Baidu, Pony Ma, founder of Tencent, and Liu Qingfeng, chairman of iFlytek, all proposed to facilitate importing overseas talents.
The hiring frenzy & the twist
The hiring frenzy must have evoked a sense of déjà vu in everyone.
The companies’ chase for AI talents recalls that for IOS development engineers when the mobile internet boomed in 2011. However, the shortage of AI talents is acuter, because it takes more time and training for an AI specialist to mature.
While the AI companies are struggling, some companies are angling for the profits from the scarcity. When the mobile internet started to take flight, many training companies flourished by shipping talents to the rising industry. They promised that a junior college student could take home over 10,000 yuan a month after one to two months’ training.
It sounds crazy, but many had happily landed positions with that offer.
The race to snag AI talents has also fueled the AI talent training business.
Julyedu.com (七月在线), an online training platform for AI talents founded by July (a person), is among them. July used to blog about the pre-employment tests on technical expertise. In 2012, July started to note that BAT has started adding data structure and algorithms to their paper tests and that there was a growing interest in algorithms and machine learning.
He was fully aware of the potential in this area and launched Julyedu.com in 2015. According to July, there are now 20,000 people taking lessons on the platform.
Learners come from different backgrounds. Half of them are postgraduates in universities and the other are current employees from tech companies, including BAT, Meituan, JD, Huawei and other tech startups.
“There are about tens of thousands people from big internet companies that take interest in machine learning, but only hundreds of them who really work in the field of data analysis can master the requisite skills.” The courses available on Julyedu.com are all entry-level courses. But the growing popularity of its courses indicates that talents are now gearing up for the lucrative roles in the AI world.
According to Alex, the high salary driven up by the scarcity won’t last for more than three years. Three years are quite enough to nurture new AI talents and for the investment frenzy in AI to cool down. Some AI startups won’t even be able to survive the AI race, so it is sure that more talents will be unleashed to the market.
Before that, the battle for AI talents isn’t likely to abate.
