Talent Market Imbalance in the Large Language Model Field: High-Tech Positions Face a Shortage, While Educational Requirements Remain High

Talent Market Imbalance in the Large Language Model Field: High-Tech Positions Face a Shortage, While Educational Requirements Remain HighAlthough the overall talent supply-demand ratio in the large language model field is 1.76, indicating a surplus of talent, according to a recent report from Maimai High-Hiring Talent Intelligence on "2024 Large Language Model Talent Report," high-tech positions, such as cloud computing talent, are extremely scarce

Talent Market Imbalance in the Large Language Model Field: High-Tech Positions Face a Shortage, While Educational Requirements Remain High

Although the overall talent supply-demand ratio in the large language model field is 1.76, indicating a surplus of talent, according to a recent report from Maimai High-Hiring Talent Intelligence on "2024 Large Language Model Talent Report," high-tech positions, such as cloud computing talent, are extremely scarce. The supply-demand ratio is only 0.33, which means there are three positions competing for one talent. The report reveals that from January to July 2024, the supply and demand of large language model talent remained stable compared to 2023, with an overall supply-demand ratio hovering around 1.7. The pure Internet industry exhibits the highest demand for large language model talent, boasting a recruitment index of 74.77, significantly surpassing other sectors.

However, despite the overall high demand, some technical positions still experience a talent shortage. Algorithm engineers represent the largest number of newly posted positions, while cloud computing, search algorithms, and large language model algorithms consistently rank among the top positions facing talent shortages for two consecutive years.

Furthermore, the report indicates that the large language model field holds relatively high educational requirements for talent, with positions requiring master's and doctoral degrees accounting for 29.66%. This percentage notably surpasses the average for the new economy, reflecting the strong demand for high-end talent in the large language model domain.

It is noteworthy that nearly 70% of professionals have already integrated large language models into their work, with 27.77% of professionals using them daily. Text generation and code generation constitute the two primary applications of large language model products, comprising 64.72% and 19.09% respectively. Notably, professionals utilizing large language models for code generation experience a more significant improvement in work efficiency, with 45% of users reporting a productivity increase of 30% or more.

Sun Tong, Chief Human Resources Officer at Mianbi Intelligence, emphasizes that AI-native thinking and the ability to flexibly utilize AI will become core competencies for future talent. Lin Fan, Founder and CEO of Maimai, acknowledges that unlike the mobile internet era, talent competition in the large language model field appears more rational, and talent considers a wider range of factors when choosing employers.

Analysis of the Current State of the Large Language Model Talent Market:

• Supply-Demand Imbalance: Although the overall talent supply-demand ratio is 1.76, signifying a surplus of talent, high-tech positions such as cloud computing talent are extremely scarce, with a supply-demand ratio of just 0.33, highlighting a prominent talent shortage.

• Highest Demand in the Internet Industry: The pure Internet industry displays the highest demand for large language model talent, with a recruitment index of 74.77, far exceeding other sectors.

• Strong Demand for Highly Educated Talent: The large language model field places relatively high educational requirements on talent, with positions requiring master's and doctoral degrees accounting for 29.66%, notably surpassing the average for the new economy.

• Widespread Adoption of Large Language Models in the Workplace: Nearly 70% of professionals have incorporated large language models into their work, with 27.77% of professionals using them daily.

• Significant Efficiency Gains in Code Generation: Professionals utilizing large language models for code generation experience a more significant improvement in work efficiency, with 45% of users reporting a productivity increase of 30% or more.

Future Trends in Talent Development:

• AI-Native Thinking: AI-native thinking and the ability to flexibly utilize AI will become core competencies for future talent.

• Rational Talent Competition: Talent competition in the large language model field appears more rational, and talent considers a wider range of factors when choosing employers.

Conclusion:

The talent market in the large language model field exhibits a supply-demand imbalance, with a shortage of high-tech position talent and a strong demand for highly skilled individuals. In the future, AI-native thinking and the ability to flexibly utilize AI will become core competencies, and talent will adopt a more rational approach when choosing employers, considering a broader range of factors.

Disclaimer: The content of this article is sourced from the internet. The copyright of the text, images, and other materials belongs to the original author. The platform reprints the materials for the purpose of conveying more information. The content of the article is for reference and learning only, and should not be used for commercial purposes. If it infringes on your legitimate rights and interests, please contact us promptly and we will handle it as soon as possible! We respect copyright and are committed to protecting it. Thank you for sharing.(Email:[email protected])