The Fierce AI Talent War Between OpenAI and Google Escalates as Salaries for AI Experts Surpass Millions

It’s crazy, it’s crazy! The battle for talent between OpenAI and Google has entered a fever pitch.

OpenAI offers the ultimate temptation to Google employees – an annual salary of US$5 million to US$10 million! And endless computing power from Microsoft!

No, the key research talents of Google’s revenge artifact Gemini model have been poached by OpenAI.

Google also took revenge, promising to give OpenAI employees a higher annual salary than the previous year’s salary, and successfully included the former OpenAI employees who developed Code Interpreter.

In China, AI talents are also being frantically robbed. Just recently, China Business News reported that the annual salary of fresh PhDs in domestic AI has risen to millions, and some are even poached before they leave school.

A Peking University professor said that before his students graduated, big companies were poaching them with millions.

The temptation of OpenAI: The stock price has soared, and there is no shortage of cores

According to foreign media The Information, the recruitment war between OpenAI and Google has intensified.

OpenAI began selling employee stock, directly increasing its valuation by nearly three times to more than $80 billion.

Taking advantage of this trend, OpenAI’s recruiters began to poach people at Google – Google’s top artificial intelligence employees were offered millions of dollars in olive branches.

OpenAI said that if you join us now, you can lock in a stock share for US$27 billion, and it will rise sharply in the future and make countless profits.

In addition, the temptation offered by OpenAI is of course not limited to stocks. The recruiter claimed that as long as you come to OpenAI, you no longer have to worry about computing resources, and there will be enough chips for developing models.

However, employees on both sides actually agree that Google is the one with the real advantage in the chip field. After all, it has invested heavily in data centers and dedicated AI chips, which have become the company’s key development directions.

To obtain chips, OpenAI must rely on a multi-billion-dollar cooperation with Microsoft.

Of course, Sam Altman is well aware of this.

According to insiders, he has told some colleagues that Google is expected to gain a computing resource advantage sometime next year, and by then, OpenAI will need more chips from Microsoft.

Google has implemented the world’s largest distributed large language model training work, involving 50,000+ TPU v5e chips

Despite this, OpenAI still has to declare that it is one of its major advantages to allow researchers to quickly use Nvidia’s chips.

The total contract is 10 million dollars, so I asked if I can come.
This is how OpenAI recruiters negotiate terms with senior Google AI researchers: If they sell their stocks, their annual salary will be about US$5 million to US$10 million.

How was this sky-high figure calculated? It was explained that this assumes that the newly recruited employees join OpenAI before the equity sale closes, and also depends on their level within OpenAI.

He specifically emphasized that Google did not have an offer of this level.

Some insiders revealed that OpenAI has recently been giving salary increases to some junior employees because salaries in the entire market have increased.

Also, OpenAI’s stock compensation is somewhat unusual.

Its shares are distributed in the form of profit units, meaning shareholders can receive returns without acquiring the company or conducting an IPO, as long as OpenAI is doing well.

Although based on OpenAI’s shareholding structure when it raised $10 billion from Microsoft earlier this year, the return on these units may be capped.

But OpenAI has told employees that it will regularly allow them to sell shares to other investors, as private companies like SpaceX do.

OpenAI’s current stock sale will be its second this year. After the tender offer is completed, it may be more difficult for OpenAI to recruit talent from Google employees, because the upside potential of the stock may be limited.

Of course, Google’s stock price is not bad either: as its advertising business gradually recovers and its cloud server rental business has become profitable, Google’s stock price has risen by nearly 50% this year.

The Information reported last month that Thrive Capital would lead the acquisition of employee-owned shares at a valuation of at least $80 billion.

OpenAI’s new valuation will be more than 60 times its annual revenue! This has also made OpenAI one of the most highly valued private companies supported by venture capital.

Google’s senior talents are all in demand
The war for talent between OpenAI and Google is intensifying and shows no sign of letting up.

Since ChatGPT launched the AI ​​​​competition, companies including Anthorpic, Meta and other companies have been competing for top researchers.

However, Google has become OpenAI’s primary target due to its deep talent pool and the publication of cutting-edge research results.

It is said that the Gemini series of models being developed by Google have been long-awaited by the whole company. After all, Gemini is going to compete with GPT-4.

OpenAI, of course, needs to take advantage of the situation.

At the end of last year, OpenAI successfully recruited more than a dozen researchers, and recently poached many key researchers from Google.

For example, Jiahui Yu, who leads the Gemini project, is very good at developing models that contain both text and images.

According to his LinkedIn profile, he joined OpenAI in October.

In fact, the smooth launch of ChatGPT was indispensable for the important role of former Google researchers, some of whom were personally recruited by Sam Altman.

Now, ChatGPT has become a multi-billion dollar business.

OpenAI’s new GPT Builder allows anyone to create GPT using natural language zero code, which will create billions of dollars in revenue

It is unbearable, and Google is certainly not idle.

People familiar with the matter revealed that Google has begun to fight back this year, recruiting some well-known researchers from OpenAI, and is willing to provide them with higher salaries than those of their former employer.

For example, according to LinkedIn information, Matt Wiethoff, a former employee who developed the ChatGPT Code Interpreter, left OpenAI in October and joined Google DeepMind.

The demand for domestic AI talents is soaring, and PhDs are being poached even before they leave their jobs.

Just recently, China Business News reported that the annual salary of fresh PhDs in domestic AI has risen to millions, and some are even poached before they leave school.

The article mentioned that a professor from a software engineering-related laboratory at Peking University said that their team has already had students who have not graduated yet, and large companies have hired millions of people to poach his people.

In this regard, Liepin Group CEO Dai Kebin said, “Nowadays, AI talents are rising. If a PhD student is in this field and has just graduated, he can still see a starting salary of 2 million, and this does not count stocks.”

This also confirms the previous statistics of Liepin Big Data Research Institute – the demand for 2023 doctoral freshmen has the largest increase in the demand for AI large models, reaching 430%; artificial intelligence ranks sixth, at 112.50%.

In addition, according to Liepin’s analysis, from January to August 2023, new domestic AIGC positions increased by 139.76% year-on-year, and the average annual salary for recruitment reached 410,900 yuan.

The top five functions with the highest number of newly created positions are algorithm engineer (15.47%), product manager (9.44%), natural language processing (4.91%), image algorithm (4.86%), and deep learning (2.37%).

Moreover, the recruitment salaries for these functions also exceed 430,000. Among them, deep learning, image algorithm, and natural language processing ranked in the top three, with 557,800, 551,000, and 533,100 respectively. Algorithm engineers and product managers ranked fourth and fifth, with 494,700 and 436,500 respectively.

Liepin said that the domestic AIGC industry can be roughly divided into infrastructure layer, model layer and application layer.

Basic layer: the construction of basic support platform, including sensors, AI chips, data services and computing platforms;

Model layer: the research and development of core technologies, mainly including algorithm models, basic frameworks, and general technologies;

Application layer: industrial application development, mainly including industry solution services, hardware products and software.

– The model level has the highest educational requirements, with master’s and doctorate accounting for over 30%

Since the basic layer and model layer focus more on technology, the job requirements for academic qualifications are also higher.

In terms of master’s and doctoral degrees, the demand for the basic layer accounts for 27.56% of the total; the model layer is 30.89%; and the application layer is 18.07%.

Among them, the demand for PhDs in the model layer accounts for the highest proportion, 3.28%, while the demand for PhDs in the basic layer and application layer does not exceed 1.5%.

– There are more positions in the high-paying segment at the model level

At the same time, the demand for higher education also brings higher salaries.

According to statistics, the proportion of positions with more than 600,000 in the model layer has even reached 20.95%, which is much higher than the 1.88% in the basic layer and 9.52% in the application layer.

In comparison, the proportion of low-salary positions is even smaller—positions below 250,000 account for only 4.76%, which is significantly less than the 13.21% of other basic levels and the 11.11% of application levels.

– The average annual salary exceeds 330,000 yuan, and the model level reaches nearly 470,000 yuan.

Specifically, the average annual recruitment salary for basic-level, model-level, and application-level positions exceeds 330,000.

Among them, the model layer has the highest number, with 466,300; followed by the application layer, with 433,500; the basic layer ranks third, with 339,200.

Google unveils: A day’s work actually takes more than “8 hours”

The competition for external talent is so fierce, and it will obviously not be too easy internally.

According to an internal memo, the average working hours of Google employees have actually exceeded the “normal” nine to five…

When a Google employee asked if the company could organize his work schedule so that he worked fewer hours on more days, an HR representative responded:

“Most salaried Google employees already work more than 8 hours on a workday. No one works at Google as a 120% full-time employee, so compressing 100% of the work schedule is not realistic.”

This summer, multiple publications reportedly interviewed a Google software engineer who earns six figures and said he only coded for an hour every morning and spent the rest of the day working on his startup.

Reports of these one-hour workdays went viral online, including from friends and family of Google employees.

In response, Google spokesperson Courtenay Mencini said in a statement that Google employees can request more flexible schedules and that requests will be reviewed based on their roles and teams.

“Like any company, there are times when our employees work more than 40 hours a week to meet deadlines or deliver products and services to our users.”

In addition, the company will consider approving 60% and 80% full-time working schedules, as well as other forms of part-time work, based on the employee’s situation and manager’s approval.

However, Google says the compressed workweek isn’t as flexible as other options the company offers, nor can it be matched to the schedules of the entire team.

Over the past two decades, Google employees have enjoyed extremely generous benefits, and these strategies have been adopted by other large technology companies to recruit talent.

However, in 2023, affected by the overall economic environment, many companies have decided to reduce some benefits.

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