By JIANG Jingling

Algorithm engineers, who once would make Asian parents proud, with top salaries and by bringing cutting-edge change to the world of technology, are now feeling the chill as the industry cools.

ZHANG Mingming was an algorithm engineer for a second-rate tech company. Last December, seeking “more space for promotion,” he reached out to headhunter LI Minghua.

Li managed to get Zhang several interviews with the big tech firms, but only small companies gave him offers. Zhang, clearly irritated, rejected them immediately.

When Zhang was laid off two months later, he once again turned to Li, but all the jobs were gone, even at the smaller companies. No one was hiring, and algorithm engineers were losing their jobs, left, right and center.

Zhang had to downgrade his expectations from “looking for promotion “to “anything stable” and finally secured a gig with a startup a few months later.

Back in 2016, when AlphaGo beat Lee Sedol in the Google DeepMind Challenge Match, everything seemed possible with deep learning AI. And the algorithm that made it possible suddenly became a huge hit in the tech industry. Everybody and anybody wanted to be a big-shot algorithm engineer.

Bytedance was one example of a company that flourished amid the boom, and the filter bubble its algorithm created changed people’s internet experience. At the same time, Douyin and Toutiao became trendy apps to “find” content that users were interested in and quickly serve it up to them.

“Back then, the annual salary of an algorithm engineer fresh out of college could reach 700,000 yuan, way higher than any other job a computer science graduate could get,” said Li.

Shaw Wang got his bachelor's degree in computer science that year, but instead of looking for a job, he decided to pursue a master’s in algorithm engineering in the US.

But when Wang came back to China three years later, he sensed a wind of change. “All of my competitors had graduated from top schools, and the ivy league didn’t make you stand out at all,” he said.

Such fierce competition was common among all the big tech firms, such as Tencent, Alibaba and their kin.

After being rejected by seven companies, it took him almost a year to find a job. In retrospect, Wang believes he made a wise decision by lowering the bar before it was too late.

In late 2021, Li felt that most companies, small or large, had become picky.

“The same position that used to accept fresh graduates now wants someone with at least five years’ experience,” he said.

Many engineers who thought they would be doing revolutionary work to push the algorithm to ever-new heights found they were simply processing data in an already established open-source platform.

Around 2017, the algorithm meant more accurate ads and efficient resource distribution. Now all that is done, where is the next breakthrough and is it worth all the cost? It is a problem that big tech and all their brainy engineers have not yet managed to sort out.

Early this year, Wang’s company sacked four algorithm engineers. Wang was kept on, not because of his skills but due to the fact that his salary was relatively low as a “junior.”

He soon found that his diminished team of three was working on the same things they had been doing before. Some of the cut and thrust - the innovation - had somehow been lost.

“From zero to one is ground-breaking, but what we do now is simply rehandling things, nothing creative,” he said.

For the big tech companies, businesses operate just fine without ever-better algorithms.

“Take automatic speech recognition, for instance,” Wang said. “It is 90 percent accurate now, so should more money be invested for the remaining 10 percent?”

For companies looking for higher profits, the simple answer is no.

Li said the new favorite product in the market for algorithm specialists was self-driving technology, with big tech scrambling to join the EV race. But how long will it last before the wheels come off? Only time will tell.