再見，區塊鏈開發者。歡迎，人工智能專家。

從雇傭數量來看，人工智能專家一職成了美國增速最快的工作崗位，至少根據領英（LinkedIn）于12月10日發布的年度新興工作崗位報告來看，確實如此。

領英的報告稱，在其職業網絡服務上的人工智能專家崗位雇傭人數在過去四年里年度增長74%。不過領英并未公布這一數據具體意味著多少工作崗位，只是表明這一崗位的需求增速超過其他新興工作崗位。

特別值得一提的是，去年排名第一位的工作崗位區塊鏈開發者，今年從清單中消失了。可以清楚地看到，這些年虛擬貨幣和區塊鏈的熱度制造了區塊鏈相關工作崗位的需求，但隨著區塊鏈熱度的消失，這種需求也隨之消失。

“曾經輝煌，但消失地也快。”領英的首席經濟學家蓋伊·伯格說。區塊鏈開發者居然沒有出現在今年的新興工作崗位清單中，伯格說這表明了公司數據的有效性，正確反映出了“失敗的趨勢，或者說什么是曇花一現。”

今年清單的第二位是“機器人工程師”，這個術語涵蓋了物理機器人工程師，以及所謂的機器人過程自動化工程師，這個時髦的科技包括了軟件自動化基本功能，例如將數據寫入清單。雇傭人數增長第三快的工作崗位是“數據科學家”。

人工智能專家這個崗位，是從曾經獨占清單鰲頭的機器學習和數據分析崗位演化而來的。伯格認為，盡管人工智能專家可能與數據科學家有類似的特點，但數據科學家的工作涉及更廣泛的數據工具或數據圖像化工具，而非只是機器學習軟件。

最需要人工智能專家的都市區包括舊金山灣區、紐約、波士頓、西雅圖和洛杉磯。最對口的行業是計算機軟件、互聯網、信息科技、高等教育和消費電子。

領英的發言人說，在獲得人工智能專家這一工作稱號之前，這類人的工作崗位主要是“軟件工程師”、“數據科學家”、“研究助理”和“數據工程師”。也就是說，相關人士可以更新他們的職位類型，加入人工智能這個詞匯，以便在人工智能蓬勃發展的時代，更好地實現自己的價值。

“談到人工智能，確實需求爆棚。”伯格說，“但我認為，發展趨勢需要把數據科學提升到下一個層級。”（財富中文網）

譯者：宣峰

Bye bye blockchain developer, hello artificial intelligence specialist.

That role, A.I. specialist, is the fastest growing U.S. job in terms of number of hires, at least according to LinkedIn, which published its annual emerging jobs report on December 10.

Hirings for A.I. specialists on the career networking service have grown 74% annually over the past four years, LinkedIn said. But it didn’t reveal how many jobs that represents, only that demand for that job role is growing faster than other emerging jobs.

What’s noteworthy about this year’s survey is that last year’s top job role, blockchain developer, is absent from the latest list. It highlights how the recent craze over cryptocurrencies and blockchain created a brief demand for blockchain-related jobs, but as the hype died down, so too did demand for people with blockchain skills.

“It was spectacular, but vanished very quickly,” LinkedIn’s principal economist Guy Berger said. The fact that blockchain developers did not make this year’s emerging job list caused Berger to say that it validates his company’s data by showing it accurately reflects “a failed trend or a flash in the pan.”

No. 2 on the list was “robotics engineer,” an umbrella term for both physical robotics and so-called robotic process automation, a trendier technology that involves software automating basic tasks like entering data into a table. The third fastest growing job in terms of hiring was “data scientist.”

A.I. specialist is an evolution of other machine-learning and data-crunching job titles that have topped the list before. Although A.I. specialists may share some traits with data scientists, the work of data scientists involves a wider set of statistical or data visualizations tools versus just machine learning software, Berger said.

The top metropolitan areas where A.I. specialists are in demand include the San Francisco Bay Area, New York, Boston, Seattle, and Los Angeles. Computer software, Internet, information technology, higher education, and consumer electronics are the industries with the biggest appetite.

The most common jobs that A.I. specialists held prior to labeling themselves with the title include “software engineer,” “data scientist,” “research assistant,” and “data engineer,” a LinkedIn spokesperson said. This suggests that people may be updating their job titles to include artificial intelligence, to put themselves in a better position to capitalize on the current A.I. boom.

“When you talk about A.I., again it’s super high in demand,” Berger said. “I think there’s more and more interest in taking data science to the next level.”