It is harder than ever to secure your first professional position, and more potential job seekers are discovering just that. There are fewer graduate-level places, fewer promotions, and ruthless competition.
But if you happen to speak the language of artificial intelligence, your future is altered overnight.
Certain twenty-somethings skip out on years of subsistence-level climbing the corporate ladder, and instead earn salaries comparable to their CEOs’, with some of them grossing over a million dollars before the age of 25.
The overall labor market has been unable to rebound for recent graduates. The Federal Reserve Bank of New York analysis showed that college graduates unemployment rate reached 4.8% last June, while the total labor-force rate was only 4%.
Of course, AI is also responsible, ironically enough, as it has been eliminating the kinds of low-skilled or entry-level jobs long regarded as stepping stones to more advanced work.
The New Fast-Track Career Path
AI expertise is so scarce that emerging workers are skipping over established tracks of advancement. Base salaries in entry-level AI positions, or those with from zero to three years of experience, increased 12% from 2024 to 2025.
This is the largest spike from an experience group, according to a report from Burtch Works, a recruiting firm specializing in data and AI specialists.
Even more impressively, workers with AI expertise are being promoted into management twice as fast as colleagues in other tech specialties. In short, it’s experience with machine learning, more so than experience in the business, that counts here.
“There is a significant salary difference between a machine-learning engineer job and a software engineer job,” says Anil K. Gupta, professor in the University of Maryland’s Robert H. Smith School of Business.
While old-fashioned software engineers may still command a respectable salary, their AI counterparts are drawing amounts that had been deemed impossible for a freshly minted graduate.
Racing to Recruit AI-Native Talent
One firm putting big money on youth AI talent is Databricks, a rapidly rising data analytics software company worth tens of billions of dollars.
CEO Ali Ghodsi explains the company intends to triple recruitment of new graduates during the current year, exactly because they are “AI-native.”
“They’re going to come in, and they’re going to be all AI-native,” explains Ghodsi. “We can’t for the life of us get the more senior people to adopt it.”
A research scientist in AI who has been with Databricks for only two years should carry a base in the $190,000-to-$260,000 tier, with high stock awards on top capable of propelling total compensation into the stratosphere.
Ghodsi forthrightly confirms there are a few workers, all under 25, already topping seven figures due to their abilities and enterprise equity.
Scale AI, another young company, has about 15% of its employees under 25. Starting salaries for incoming recruits are generally $200,000 or more, and the company has had to turn back intense poaching attempts from rivals looking to steal young talent.
“We’re eager to hire AI-native professionals, and many of those candidates are early in their careers,”
says Ashli Shiftan, people leader at Scale AI. The company has also threatened litigation against rivals who look to poach their youngest high-potentials.
From Teacher’s Desk to Corner Office, Practically Overnight
The individual stories of young professionals reveal just how deeply the career escalator is being rewritten through artificial intelligence.
Lily Ma, who graduated from Carnegie Mellon with a degree in computer science with an artificial intelligence track when she was just 22 years old, applied to more than 30 jobs right out of graduation.
With a research background and an internship at Tesla, she found a job with Scale AI. She has turned down offers with a 1% equity stake in a startup company. “I did notice that having research experience helps a lot,” she admits.
Second is Cyril Gorlla, who was 23 when he co-founded Google-financed startup CTGT, which creates AI safety and risk-management software. At an average age of 21 among employees, the company watched some of its employees’ equity shares increase to half a million dollars.
Gorlla has watched the talent pool just continue to get younger: “I’ve even had a 16-year-old who’s authored an AI paper contact me via email to join the team. I certainly didn’t do things like that a few years ago.”
Stanford University’s Professor Jure Leskovec has watched Ph.D. students abandon academia in their early years when tech giants come knocking with handsome pay offers. “The number of zeros is pretty big,” he said.
Some of the hires are stellar researchers, but others are merely master practitioners of AI tool utilization in ways never before possible, making them superior to the more traditional programmers.
The Million-Dollar Question
Not all young AI specialists are reaching millionaire status, naturally, but their compensation eclipses most first jobs manyfold. Some machine-learning engineer roles with less than a year of experience command above $200,000.
These numbers do not just consist of base pay. Stock options and equity compensation are having an enormous impact in driving compensation into the high six figures.
For young engineers in their early 20s, these packages are not just life-changing but career-making, allowing them to amass riches typically reserved for late-term executives decades their seniors.
The Divided Market
Yet the boom is unevenly distributed. As Leskovec points out, there is a sharp divide between those who are writing core AI technologies and those who are merely learning to use the technologies with maximum efficiency.
The first set of people, Ph.D.-scale researchers and engineers, are fetching astronomical salaries. The second set, efficient users of AI who adapt rapidly, is also in high demand, but the differential pay vis-à-vis traditional programmers is increasing.
That gap is reshaping career advice for young workers. For decades, the safe bet was a degree in computer science and a slow climb up the software engineering ranks.
Today, the surest way to job security and rapid advancement might be mastering AI, whether through formal education or self-directed projects.
What Is the Next Step?
While companies struggle to infuse AI in everything from customer service to biotech research, AI skill interest does not appear to wane.
Startups such as Scale AI and Databricks are hiring young pros at a hyperactive clip, while startups led by freshly minted college grads are attracting capital from Google and others.
The excitement has also generated fears, however.
Will there be lasting growth when so much money is focused on workers so young? Will there continue to be an ongoing “AI-native” leadership, or do more seasoned workers find ways to overtake them? Is this AI skill just a market bubble that is going to burst at some point?
For now, there’s one thing sure: the job market might be tough sledding for most young adults, but for linguists who specialize in machine learning, the 20s are the new 40s, or so far, as salaries go.
As more businesses compete over scarce AI talent, salaries just might keep getting fatter, too.
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