Futures
Access hundreds of perpetual contracts
TradFi
Gold
One platform for global traditional assets
Options
Hot
Trade European-style vanilla options
Unified Account
Maximize your capital efficiency
Demo Trading
Introduction to Futures Trading
Learn the basics of futures trading
Futures Events
Join events to earn rewards
Demo Trading
Use virtual funds to practice risk-free trading
Launch
CandyDrop
Collect candies to earn airdrops
Launchpool
Quick staking, earn potential new tokens
HODLer Airdrop
Hold GT and get massive airdrops for free
Launchpad
Be early to the next big token project
Alpha Points
Trade on-chain assets and earn airdrops
Futures Points
Earn futures points and claim airdrop rewards
Hello, the new AI profession: Artificial Intelligence Trainer. Be a good AI "translator."
Answering complex questions, you can quickly get the results of your computational reasoning—artificial intelligence has already become a “good helper” for many people in their work. But in practice, it’s not easy for artificial intelligence to truly understand a person’s intent. And within this process, the “new profession” of an AI trainer plays the role of a “translator” that helps artificial intelligence do its job well.
In February 2020, “AI trainer” was included as a new profession in the Classified Dictionary of Occupations of the People’s Republic of China, covering two job types: data labeler and artificial intelligence algorithm tester. After passing the exam, trainees can obtain an AI trainer professional skills certificate.
In Shanghai, this new profession has been listed in the catalog of occupations (job types) for urgently needed and scarce high-skilled talent, as well as key-supported skill talent. In 2025, Shanghai cumulatively participated in AI trainer evaluations 16.3k person-times, and 10.9k professional skills certificates were obtained through the evaluations.
Hu Shengxiang, who works at the R&D workstation of Ideal Information Industry (Group) Co., Ltd. in Shanghai, leads his team in optimizing algorithmic large models for vertical domains in his day-to-day work, playing the role of a “guardian of the final mile of AI product implementation.”
Hu Shengxiang saw the news about the new profession of “AI trainer,” which sparked the idea of “getting certified” to improve himself.
In his view, AI development has now shifted from being model-centered to being data-centered. “From an industry perspective, simply tuning algorithms has already touched the ‘industry ceiling.’ In the future, high-quality data and fine-grained feedback mechanisms will be the deciding factors.”
During training, Hu Shengxiang found that the hands-on portion of AI trainer training courses is closely connected to the industry. For example, the course requires that, based on specific business scenarios such as medical data analysis, trainees develop data cleaning rules and learn how to perform parameter configuration and status monitoring during model training.
“During the learning process, my perspective shifted from a research viewpoint to an industrial one. I gained a deeper understanding of how to build high-quality data and how to design efficient labeling strategies. It also strengthened my ‘end-to-end’ capability—from bottom-layer data governance to top-layer algorithm weights.” Hu Shengxiang said.
An AI trainer, Hu Shengxiang, is coordinating with his team during work. Xinhua News Agency reporter Zhou Rui photo
“Artificial intelligence industry development is happening rapidly, and the demand for hiring positions like AI trainers in Shanghai is growing by more than 30%.” Li Na, general manager of Ideal Information Industry (Group) Co., Ltd. in Shanghai, found that job seekers who have obtained AI trainer certification have noticeably faster onboarding speeds when handling complex projects in real-world scenarios than other candidates. Therefore, during the hiring process, companies will also place particular emphasis on AI-related certificates. “After they join the company, we will also assign them mentors and provide 2 to 4 weeks of deep pre-job training to help them integrate into the team more quickly and understand business logic.”
Li Na said that in the future, AI trainers will develop in the direction of “professionalization and scenario-based specialization.” Not only will the positions be further subdivided, but we may also see roles such as “natural language speech processing trainer” and “visual AI trainer.” They will also further emphasize deep integration with vertical industries such as finance, healthcare, and manufacturing. Meanwhile, as the importance of AI governance continues to rise, related positions may also emerge with “new faces” such as “data evaluators” and “data compliance officers.” (Reporters Zhou Rui and Ding Ting)