Nvidia CEO Jensen Huang has said that he personally reviews the compensation of each of the 42,000 employees of the company. Speaking at the All-in Podcast during the AI-centered panel discussion, Huang described the process as a central part of its management strategy, which has benefited the company at every level, including its top officials.
Huang explained that he manages to make time for salary review despite his program. He uses machine learning tools and other techniques to help process data every month. He said, “I review everyone’s compensation till this day, at the end of every cycle. They send me everyone’s recommended Comp. I pass through the entire company. I sort through all 42,000 employees, and 100% time I increase the cost of the company on OPEX,” he said.
The NVIDIA chief also speculated that he reserves a hidden stock options for rewarding high -performing employees. Without confirming such a reserve, he emphasized his trust in competitive salary. “If you take care of people, everything else takes care of itself,” he said. Huang said that this approach has helped to maintain and reward leadership talent, given that he has created a “more billionaire” on his management team than any other CEO in the world. “They are just fixing. Don’t be sad for anyone on my layer,” they commented.
This strategy seems to be paid for the senior leadership of Nvidia. The rapid increase in the price of the company’s stock recently pushed three of its board members into the billionaire rank. Last year, Huang himself entered the Forbes list of the world’s top 10 most wealthy persons for the first time. He said that his goal is to compensate employees at all levels at all levels, not only the top level.
In the same podcast, Huang talked about the power of mid-shaped, well-funded teams to complete major technical successes. He cited examples of Openai, which began with about 150 employees and China’s Deepsek, with a similar headcon. “This is not a small team. It’s a good size team with the right infrastructure … If you are ready to pay, then say, $ 20 billion, $ 30 billion, 150 AI researchers to buy a startup with the researchers, why don’t you pay one?” He said.
Huang argued that with correct funding and resources, teams of that size can “make Wonders” in the field of AI. His comments underline their confidence that investing in talent, whether in small expert groups or in the entire organization, is the foundation for long -term success.
