AI engineers paid higher in China than Silicon Valley

Alibaba joined hands with KrASIA’s parent company, 36Kr, to launch ‘AI Masterclass’. This article summarizes the key takeaways on employing AI engineers.

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AI engineers paid higher in China than Silicon Valley

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Tech startups are paying high salaries to AI engineers. This might hinder the growth because there is a dilemma: underpaying may affect employees’ performance while overpaying may affect the company’s sustainability.

In August 2018, Alibaba joined hands with KrASIA’s parent company, 36Kr, to launch ‘AI Masterclass’, a four-day initiative to educate CEOs about Artificial Intelligence. Allen Zhu, managing director of GSR Ventures, shared investment trends in the field of AI and posed a question on whether it is too expensive to hire AI engineers and how do companies balance the salary gap with other employees. Here are the key takeaways from the masterclass:

Headhunting is not enough

It is not easy to find talented engineers. In addition to the usual recruitment channels such as regular recruitment websites and headhunting, recruitment can be done through events such as competitions.

It is cheaper to hire talents from Silicon Valley

Although a large number of AI companies are registered in China, talents can be recruited from overseas. In fact, AI engineers are cheaper to hire in Silicon Valley than in China. Recruiting a former BAT (Baidu, Alibaba, and Tencent) employee often requires 2 to 3 million RMB, because Chinese tech companies are willing to pay a high premium for AI engineers from BAT (what they call P9 and P10 employees)

Partnerships with universities and research organizations

In addition to the in-house team, it is also possible to work with external research institutes. Many CEOs believe that they can cooperate with research institutes or universities and receive technical support with grants are available for relevant funds for R&D.  In general, startups prefer to have partnerships with research organizations than universities.

Open source technology is available

There are technologies and solutions that are already developed and standardized by other companies.  Startups need to know how to apply these tools.

Ensuring productivity

Obtaining enough data for valuable insights

AI technology relies on algorithm, computing power and data. It is not possible to achieve valuable results with little data. Moreover, AI engineers are only interested when there is a sizable amount of data to digest.

Providing a correct mindset

Startups often compete with large companies and other companies for talents. Entrepreneurs should make these AI engineers understand the mission and vision of the company so that employees really know what the company is doing and how they can contribute.

Retaining good employees

Establish R&D team

In order to explain the high salary gap between AI engineers and other employees, companies can set up another subsidiary or R&D department. It does not matter if the department is small, as it helps achieve a common understanding that AI employees deserve high salaries.

Provide shares and options

In addition to salary, startups can consider giving out employee shares or options to entice them to work harder for future profits. This also enables ownership among these engineers.