Laid-off techies face ‘sense of impending doom’ with job cuts at highest since dot-com crash
The Google office in New York on February 2, 2023.
Ed Jones | Afp | Getty Images
Allison Croisant, a data scientist with about a decade of experience in technology, was laid off by PayPal earlier this year, joining the masses of unemployed across her industry. Croisant has one word to describe the process of looking for a job right now: “Insane.”
“Everybody else is also getting laid off,” said Croisant, who lives in Omaha, Nebraska, where she worked remotely for PayPal.
Her sentiment is reflected in the numbers. Since the start of the year, more than 50,000 workers have been laid off from over 200 tech companies, according to tracking website Layoffs.fyi. It’s a continuation of the predominant theme of 2023, when more than 260,000 workers across nearly 1,200 tech companies lost their jobs.
Alphabet, Amazon, Meta and Microsoft have all taken part in the downsizing this year, along with eBay, Unity Software, SAP and Cisco. Wall Street has largely cheered on the cost-cutting, sending many tech stocks to record highs on optimism that spending discipline coupled with efficiency gains from artificial intelligence will lead to rising profits. PayPal announced in January that it was eliminating 9% of its workforce, or about 2,500 jobs.
For the tens of thousands of people in Croisant’s position, the path toward reemployment is daunting. All told, 2023 was the second-biggest year of cuts on record in the technology sector, behind only the dot-com crash in 2001, according to outplacement firm Challenger, Gray & Christmas. Not since the spectacular flameouts of Pets.com, eToys and Webvan have so many tech workers lost their jobs in such a short period of time.
Last month’s job cut count was the highest of any February since 2009, when the financial crisis forced companies into cash preservation mode.
CNBC spoke to a dozen people who have been laid off from tech jobs in the past year or so about their experiences navigating the labor market. Some spoke on the condition that CNBC not use their names or write about the details of their situation. Taken together, they paint a picture of an increasingly competitive market with job listings that include exacting requirements for qualification and come with lower pay than their prior gigs.
It’s a particularly confounding situation for software developers and data scientists, who just a couple of years ago had some of the most marketable and highly valued skills on the planet, and are now considering whether they need to exit the industry to find employment.
“The market isn’t what it once was,” Roger Lee, creator of Layoffs.fyi, said in an email. “To secure a new position, many salespeople and recruiters are leaving tech entirely. Even engineers are compromising — accepting roles with less stability, a tougher work environment, or lower pay and benefits.”
Lee said tech salaries have “largely stagnated” in the last two years, citing data from Comprehensive.io, a compensation tracker he recently helped launch.
Croisant’s job search involved applying for some positions that had racked up hundreds of applicants. She could see that data using LinkedIn’s Talent Insights platform, which shows how many people are vying for an open role.
Additionally, some listings required applicants to have advanced degrees or professional experience in machine learning and artificial intelligence, a new development in Croisant’s experience on the job market.
During five weeks of job hunting, Croisant said she applied to 48 openings and landed two interviews. She finally opted to accept a lower-level data analyst role and a roughly $3,000 reduction in her base pay to take a contract role starting next month at a financial technology company.
“This was an absolutely terrifying experience for me, and I’m not sure if I’ll ever truly feel secure in a job again,” Croisant said. “But I’m still one of the lucky ones in the end. I have friends who’ve been looking for months and still haven’t found anything.”
‘It’s humbling’
Krysten Powers was laid off in January from travel tech startup Flyr after two years in marketing at the company. She said navigating the current labor market is like a full-time job, “sometimes even harder.”
“You’re putting out resumes and getting almost immediate rejections,” said Powers, who’s worked in marketing for a decade. “It does take a toll on your confidence and you get this sort of imposter syndrome.”
Powers lives with her husband and two kids in the small town of Natchez, Mississippi. A month before she lost her job, her family bought a new house. Powers said moving isn’t an option, and she’s only considering remote roles in marketing. However, she is willing to accept a pay cut.
“It’s humbling for sure,” she said.
Google Headquarters is seen in Mountain View, California, United States on May 15, 2023.
Tayfun Coskun | Anadolu Agency | Getty Images
The same dynamics are playing out across the industry, even for former employees of Google, which was long considered the home of Silicon Valley’s elite talent.
Christopher Fong, who worked at Google from 2006 to 2015, is the founder of a group called Xoogler.co, which seeks to provide help for people laid off from the internet company. The 9-year-old organization, consisting of thousands of Google alumni and current staffers, offers peer support and hundreds of in-person events.
In January, Google eliminated several hundred positions across its hardware, central engineering and Google Assistant teams. A year earlier, the company cut 12,000 jobs, or roughly 6% of its full-time workforce.
Fong said the “biggest challenge” today for many ex-Google employees is finding a job that maintains their previous level of pay.
Michael Kascsak, who was laid off by Google in March of last year, took a different approach to his job search.
Kascsak said he welcomed a pay cut to start as head of talent acquisition for veterinary business CityVet in January after applying for hundreds of jobs. He acknowledged that his previous employer had set exceptionally high compensation expectations.
“I went into this knowing I had been fortunate to work at a company that paid at the top percentile and I’m a realist. I prepared myself to be flexible,” said Kascsak, who lives in Austin, Texas, and previously worked in talent sourcing for Google. “I’m fine with the pay now because I’m in the environment I want to be in with great people.”
Tech is a notable outlier in a labor market that’s been largely steady over the past two years. Nationwide, the unemployment rate ticked up to 3.9% in February from 3.7% each of the prior three months. It’s been mostly in that range since early 2022. The U.S. economy added 275,000 jobs in February, topping 200,000 for a third straight month.
Booming market for AI engineers
Sentiment indexes are mixed. Job review website Glassdoor’s Employee Confidence Index, which gauges how employees feel about their employer’s six-month business outlook, sank to its lowest level in February since its sentiment data first began in 2016. Among tech workers, discussions about layoffs on Glassdoor have more than quadrupled in the past two years, and were up 12% last month compared with a year earlier.
However, ZipRecruiter’s Job Seeker Confidence Index has been rising since mid-2023, and increased to its highest level in the fourth quarter since the second quarter of 2022.
Even within tech, there’s a vast divide in the current market. Lee of Layoffs.fyi said AI is driving a “return to rapid hiring and expansion,” even as layoffs continue elsewhere. Salaries for AI engineers rose 12% from the third to fourth quarter last year, and the average salary for a senior AI engineer nationally is more than $190,000, according to Comprehensive.io.
Amit Mittal was laid off from AI lending company Upstart
Amit Mittal
Amit Mittal has been on both sides of the employment market — previously as a hiring manager and now as a job seeker.
In November, Mittal was laid off from AI lending company Upstart, where he worked as a software engineering manager, often overseeing interviews. Mittal said he witnessed the hiring process become “a lot more demanding” as layoffs surged.
“There was a lot more pressure on us to basically raise the bar higher and higher,” he said. “Somebody with a four-year experience in the past would have had a pretty good chance at getting a good job. But now they’re competing against people who have six, seven, eight years of experience for the same position.”
Mittal, who’s from India and has lived in the Chicago area since 2007, has lately been subject to a very different kind of pressure. Under his H-1B visa, Mittal had only 60 days from the official end of his employment to find a new job in the tech industry in order to stay in the country.
“If for four months, I have to pay my bills by driving an Uber or working at McDonald’s flipping burgers, that’s fine,” he said. “But that mechanism doesn’t exist for me.”
Mittal has now successfully petitioned to obtain a separate B-2 tourist visa, giving him an extra six months to find new employment. It wasn’t a cheap effort, though. He estimated he spent around $8,000 on legal and administrative costs tied to his submission.
All the while, Mittal said he’s applied for about 110 jobs to no avail. He attributed the dearth of success to employers’ reluctance or inability to sponsor visa holders.
“It seems like the possibilities are pretty slim right now, even though I see hundreds of postings every single day,” Mittal said.
Bill Vezey was laid off by eBay in January following a 13-year career as a software engineer at the online retailer. He said he’s learning the rules of the “new game,” and they’re much different than he remembers.
“Attainability is not just a numbers game,” said Vezey, 64, who lives in Santa Cruz, California. “It is a combination of how well you brand yourself, about your access through networking to any given position — to the hidden job market.”
Vezey said he hopes to be rehired at his longtime employer and wants to remain in tech.
“I am kind of an incurable optimist, despite what 60-odd years of living have brought,” he said.
Like many of those who spoke to CNBC, Powers said she spends her days tailoring her resume for openings, scanning online job boards and applying for newly posted positions. She networks by contacting a recruiter or hiring manager connected to each role, though she said some recruiters have ghosted her as quickly as they’ve expressed interest.
She’s had a few interviews, and turned down one job offer. That position would’ve required her to go to an office while taking a more than 50% pay cut from her previous job. And she’d have to find child care.
“There’s a sense of impending doom,” Powers said. “There is a point where the money runs out and the options become really bleak.”
Still, Powers said she’s trying to stay optimistic, “because giving up is not going to get me a job.”
— CNBC’s Jennifer Elias contributed to this report.
WATCH: Why widespread tech layoffs keep happening despite a strong economy
Technology
AI research takes a backseat to profits as Silicon Valley prioritizes products over safety, experts say
Sam Altman, co-founder and CEO of OpenAI and co-founder of Tools for Humanity, participates remotely in a discussion on the sidelines of the IMF/World Bank Spring Meetings in Washington, D.C., April 24, 2025.
Brendan Smialowski | AFP | Getty Images
Not long ago, Silicon Valley was where the world’s leading artificial intelligence experts went to perform cutting-edge research.
Meta, Google and OpenAI opened their wallets for top talent, giving researchers staff, computing power and plenty of flexibility. With the support of their employers, the researchers published high-quality academic papers, openly sharing their breakthroughs with peers in academia and at rival companies.
But that era has ended. Now, experts say, AI is all about the product.
Since OpenAI released ChatGPT in late 2022, the tech industry has shifted its focus to building consumer-ready AI services, in many cases prioritizing commercialization over research, AI researchers and experts in the field told CNBC. The profit potential is massive — some analysts predict $1 trillion in annual revenue by 2028. The prospective repercussions terrify the corner of the AI universe concerned about safety, industry experts said, particularly as leading players pursue artificial general intelligence, or AGI, which is technology that rivals or exceeds human intelligence.
In the race to stay competitive, tech companies are taking an increasing number of shortcuts when it comes to the rigorous safety testing of their AI models before they are released to the public, industry experts told CNBC.
James White, chief technology officer at cybersecurity startup CalypsoAI, said newer models are sacrificing security for quality, that is, better responses by the AI chatbots. That means they’re less likely to reject malicious kinds of prompts that could cause them to reveal ways to build bombs or sensitive information that hackers could exploit, White said.
“The models are getting better, but they’re also more likely to be good at bad stuff,” said White, whose company performs safety and security audits of popular models from Meta, Google, OpenAI and other companies. “It’s easier to trick them to do bad stuff.”
The changes are readily apparent at Meta and Alphabet, which have deprioritized their AI research labs, experts say. At Facebook’s parent company, the Fundamental Artificial Intelligence Research, or FAIR, unit has been sidelined by Meta GenAI, according to current and former employees. And at Alphabet, the research group Google Brain is now part of DeepMind, the division that leads development of AI products at the tech company.
CNBC spoke with more than a dozen AI professionals in Silicon Valley who collectively tell the story of a dramatic shift in the industry away from research and toward revenue-generating products. Some are former employees at the companies with direct knowledge of what they say is the prioritization of building new AI products at the expense of research and safety checks. They say employees face intensifying development timelines, reinforcing the idea that they can’t afford to fall behind when it comes to getting new models and products to market. Some of the people asked not to be named because they weren’t authorized to speak publicly on the matter.
Mark Zuckerberg, CEO of Meta Platforms, during the Meta Connect event in Menlo Park, California, on Sept. 25, 2024.
David Paul Morris | Bloomberg | Getty Images
Meta’s AI evolution
When Joelle Pineau, a Meta vice president and the head of the company’s FAIR division, announced in April that she would be leaving her post, many former employees said they weren’t surprised. They said they viewed it as solidifying the company’s move away from AI research and toward prioritizing developing practical products.
“Today, as the world undergoes significant change, as the race for AI accelerates, and as Meta prepares for its next chapter, it is time to create space for others to pursue the work,” Pineau wrote on LinkedIn, adding that she will formally leave the company May 30.
Pineau began leading FAIR in 2023. The unit was established a decade earlier to work on difficult computer science problems typically tackled by academia. Yann LeCun, one of the godfathers of modern AI, initially oversaw the project, and instilled the research methodologies he learned from his time at the pioneering AT&T Bell Laboratories, according to several former employees at Meta. Small research teams could work on a variety of bleeding-edge projects that may or may not pan out.
The shift began when Meta laid off 21,000 employees, or nearly a quarter of its workforce, starting in late 2022. CEO Mark Zuckerberg kicked off 2023 by calling it the “year of efficiency.” FAIR researchers, as part of the cost-cutting measures, were directed to work more closely with product teams, several former employees said.
Two months before Pineau’s announcement, one of FAIR’s directors, Kim Hazelwood, left the company, two people familiar with the matter said. Hazelwood helped oversee FAIR’s NextSys unit, which manages computing resources for FAIR researchers. Her role was eliminated as part of Meta’s plan to cut 5% of its workforce, the people said.
Joelle Pineau of Meta speaks at the Advancing Sustainable Development through Safe, Secure, and Trustworthy AI event at Grand Central Terminal in New York, Sept. 23, 2024.
Bryan R. Smith | Via Reuters
OpenAI’s 2022 launch of ChatGPT caught Meta off guard, creating a sense of urgency to pour more resources into large language models, or LLMs, that were captivating the tech industry, the people said.
In 2023, Meta began heavily pushing its freely available and open-source Llama family of AI models to compete with OpenAI, Google and others.
With Zuckerberg and other executives convinced that LLMs were game-changing technologies, management had less incentive to let FAIR researchers work on far-flung projects, several former employees said. That meant deprioritizing research that could be viewed as having no impact on Meta’s core business, such as FAIR’s previous health care-related research into using AI to improve drug therapies.
Since 2024, Meta Chief Product Officer Chris Cox has been overseeing FAIR as a way to bridge the gap between research and the product-focused GenAI group, people familiar with the matter said. The GenAI unit oversees the Llama family of AI models and the Meta AI digital assistant, the two most important pillars of Meta’s AI strategy.
Under Cox, the GenAI unit has been siphoning more computing resources and team members from FAIR due to its elevated status at Meta, the people said. Many researchers have transferred to GenAI or left the company entirely to launch their own research-focused startups or join rivals, several of the former employees said.
While Zuckerberg has some internal support for pushing the GenAI group to rapidly develop real-world products, there’s also concern among some staffers that Meta is now less able to develop industry-leading breakthroughs that can be derived from experimental work, former employees said. That leaves Meta to chase its rivals.
A high-profile example landed in January, when Chinese lab DeepSeek released its R1 model, catching Meta off guard. The startup claimed it was able to develop a model as capable as its American counterparts but with training at a fraction of the cost.
Meta quickly implemented some of DeepSeek’s innovative techniques for its Llama 4 family of AI models that were released in April, former employees said. The AI research community had a mixed reaction to the smaller versions of Llama 4, but Meta said the biggest and most powerful Llama 4 variant is still being trained.
The company in April also released security and safety tools for developers to use when building apps with Meta’s Llama 4 AI models. These tools help mitigate the chances of Llama 4 unintentionally leaking sensitive information or producing harmful content, Meta said.
“Our commitment to FAIR remains strong,” a Meta spokesperson told CNBC. “Our strategy and plans will not change as a result of recent developments.”
In a statement to CNBC, Pineau said she is enthusiastic about Meta’s overall AI work and strategy.
“There continues to be strong support for exploratory research and FAIR as a distinct organization in Meta,” Pineau said. “The time was simply right for me personally to re-focus my energy before jumping into a new adventure.”
Meta on Thursday named FAIR co-founder Rob Fergus as Pineau’s replacement. Fergus will return to the company to serve as a director at Meta and head of FAIR, according to his LinkedIn profile. He was most recently a research director at Google DeepMind.
“Meta’s commitment to FAIR and long term research remains unwavering,” Fergus said in a LinkedIn post. “We’re working towards building human-level experiences that transform the way we interact with technology and are dedicated to leading and advancing AI research.”
Demis Hassabis, co-founder and CEO of Google DeepMind, attends the Artificial Intelligence Action Summit at the Grand Palais in Paris, Feb. 10, 2025.
Benoit Tessier | Reuters
Google ‘can’t keep building nanny products’
Google released its latest and most powerful AI model, Gemini 2.5, in March. The company described it as “our most intelligent AI model,” and wrote in a March 25 blog post that its new models are “capable of reasoning through their thoughts before responding, resulting in enhanced performance and improved accuracy.”
For weeks, Gemini 2.5 was missing a model card, meaning Google did not share information about how the AI model worked or its limitations and potential dangers upon its release.
Model cards are a common tool for AI transparency.
A Google website compares model cards to food nutrition labels: They outline “the key facts about a model in a clear, digestible format,” the website says.
“By making this information easy to access, model cards support responsible AI development and the adoption of robust, industry-wide standards for broad transparency and evaluation practices,” the website says.
Google wrote in an April 2 blog post that it evaluates its “most advanced models, such as Gemini, for potential dangerous capabilities prior to their release.” Google later updated the blog to remove the words “prior to their release.”
Without a model card for Gemini 2.5, the public had no way of knowing which safety evaluations were conducted or whether DeepMind checked for dangerous capabilities at all.
In response to CNBC’s inquiry on April 2 about Gemini 2.5’s missing model card, a Google spokesperson said that a “tech report with additional safety information and model cards are forthcoming.” Google published an incomplete model card on April 16 and updated it on April 28, more than a month after the AI model’s release, to include information about Gemini 2.5’s “dangerous capability evaluations.”
Those assessments are important for gauging the safety of a model — whether people can use the models to learn how to build chemical or nuclear weapons or hack into important systems. These checks also determine whether a model is capable of autonomously replicating itself, which could lead to a company losing control of it. Running tests for those capabilities requires more time and resources than simple, automated safety evaluations, according to industry experts.
Google co-founder Sergey Brin
Kelly Sullivan | Getty Images Entertainment | Getty Images
The Financial Times in March reported that Google DeepMind CEO Demis Hassabis had installed a more rigorous vetting process for internal research papers to be published. The clampdown at Google is particularly notable because the company’s “Transformers” technology gained recognition across Silicon Valley through that type of shared research. Transformers were critical to OpenAI’s development of ChatGPT and the rise of generative AI.
Google co-founder Sergey Brin told staffers at DeepMind and Gemini in February that competition has accelerated and “the final race to AGI is afoot,” according to a memo viewed by CNBC. “We have all the ingredients to win this race but we are going to have to turbocharge our efforts,” he said in the memo.
Brin said in the memo that Google has to speed up the process of testing AI models, as the company needs “lots of ideas that we can test quickly.”
“We need real wins that scale,” Brin wrote.
In his memo, Brin also wrote that the company’s methods have “a habit of minor tweaking and overfitting” products for evaluations and “sniping” the products at checkpoints. He said employees need to build “capable products” and to “trust our users” more.
“We can’t keep building nanny products,” Brin wrote. “Our products are overrun with filters and punts of various kinds.”
A Google spokesperson told CNBC that the company has always been committed to advancing AI responsibly.
“We continue to do that through the safe development and deployment of our technology, and research contributions to the broader ecosystem,” the spokesperson said.
Sam Altman, CEO of OpenAI, is seen through glass during an event on the sidelines of the Artificial Intelligence Action Summit in Paris, Feb. 11, 2025.
Aurelien Morissard | Via Reuters
OpenAI’s rush through safety testing
The debate of product versus research is at the center of OpenAI’s existence. The company was founded as a nonprofit research lab in 2015 and is now in the midst of a contentious effort to transform into a for-profit entity.
That’s the direction co-founder and CEO Sam Altman has been pushing toward for years. On May 5, though, OpenAI bowed to pressure from civic leaders and former employees, announcing that its nonprofit would retain control of the company even as it restructures into a public benefit corporation.
Nisan Stiennon worked at OpenAI from 2018 to 2020 and was among a group of former employees urging California and Delaware not to approve OpenAI’s restructuring effort. “OpenAI may one day build technology that could get us all killed,” Stiennon wrote in a statement in April. “It is to OpenAI’s credit that it’s controlled by a nonprofit with a duty to humanity.”
But even with the nonprofit maintaining control and majority ownership, OpenAI is speedily working to commercialize products as competition heats up in generative AI. And it may have rushed the rollout of its o1 reasoning model last year, according to some portions of its model card.
Results of the model’s “preparedness evaluations,” the tests OpenAI runs to assess an AI model’s dangerous capabilities and other risks, were based on earlier versions of o1. They had not been run on the final version of the model, according to its model card, which is publicly available.
Johannes Heidecke, OpenAI’s head of safety systems, told CNBC in an interview that the company ran its preparedness evaluations on near-final versions of the o1 model. Minor variations to the model that took place after those tests wouldn’t have contributed to significant jumps in its intelligence or reasoning and thus wouldn’t require additional evaluations, he said. Still, Heidecke acknowledged that OpenAI missed an opportunity to more clearly explain the difference.
OpenAI’s newest reasoning model, o3, released in April, seems to hallucinate more than twice as often as o1, according to the model card. When an AI model hallucinates, it produces falsehoods or illogical information.
OpenAI has also been criticized for reportedly slashing safety testing times from months to days and for omitting the requirement to safety test fine-tuned models in its latest “Preparedness Framework.”
Heidecke said OpenAI has decreased the time needed for safety testing because the company has improved its testing effectiveness and efficiency. A company spokesperson said OpenAI has allocated more AI infrastructure and personnel to its safety testing, and has increased resources for paying experts and growing its network of external testers.
In April, the company shipped GPT-4.1, one of its new models, without a safety report, as the model was not designated by OpenAI as a “frontier model,” which is a term used by the tech industry to refer to a bleeding-edge, large-scale AI model.
But one of those small revisions caused a big wave in April. Within days of updating its GPT-4o model, OpenAI rolled back the changes after screenshots of overly flattering responses to ChatGPT users went viral online. OpenAI said in a blog post explaining its decision that those types of responses to user inquiries “raise safety concerns — including around issues like mental health, emotional over-reliance, or risky behavior.”
OpenAI said in the blogpost that it opted to release the model even after some expert testers flagged that its behavior “‘felt’ slightly off.”
“In the end, we decided to launch the model due to the positive signals from the users who tried out the model. Unfortunately, this was the wrong call,” OpenAI wrote. “Looking back, the qualitative assessments were hinting at something important, and we should’ve paid closer attention. They were picking up on a blind spot in our other evals and metrics.”
Metr, a company OpenAI partners with to test and evaluate its models for safety, said in a recent blog post that it was given less time to test the o3 and o4-mini models than predecessors.
“Limitations in this evaluation prevent us from making robust capability assessments,” Metr wrote, adding that the tests it did were “conducted in a relatively short time.”
Metr also wrote that it had insufficient access to data that would be important in determining the potential dangers of the two models.
The company said it wasn’t able to access the OpenAI models’ internal reasoning, which is “likely to contain important information for interpreting our results.” However, Metr said, “OpenAI shared helpful information on some of their own evaluation results.”
OpenAI’s spokesperson said the company is piloting secure ways of sharing chains of thought for Metr’s research as well as for other third-party organizations.
Steven Adler, a former safety researcher at OpenAI, told CNBC that safety testing a model before it’s rolled out is no longer enough to safeguard against potential dangers.
“You need to be vigilant before and during training to reduce the chance of creating a very capable, misaligned model in the first place,” Adler said.
He warned that companies such as OpenAI are backed into a corner when they create capable but misaligned models with goals that are different from the ones they intended to build.
“Unfortunately, we don’t yet have strong scientific knowledge for fixing these models — just ways of papering over the behavior,” Adler said.
WATCH: OpenAI closes $40 billion funding round, largest private tech deal on record
Omar Marques | Sopa Images | Lightrocket | Getty Images
Shares of stock brokerage platform eToro popped in their Nasdaq debut on Wednesday after the company raised almost $310 million in its initial public offering.
The stock opened at $69.69, or 34% above its IPO, pushing its market cap to $5.6 billion. Shares were last up more than 40%.
The Israel-based company sold nearly six million shares at $52 each, above the expected range of $46 to $50. Almost six million additional shares were sold by existing investors. At the IPO price, the company was valued at roughly $4.2 billion.
Wall Street is looking to the Robinhood competitor for signs of renewed interest in IPOs after an extended drought. Many investors saw President Donald Trump’s return to the White House as a catalyst before tariff concerns led companies to delay their plans.
Etoro isn’t the only company attempting to test the waters. Fintech company Chime filed its prospectus with the U.S. Securities and Exchange Commission on Tuesday, while digital physical therapy company Hinge Health kickstarted its IPO roadshow, and said in a filing it aims to raise up to $437 million in its offering.
EToro had previously filed to go public in 2021 through a merger with a special purpose acquisition company, or SPAC, that would have valued it at more than $10 billion. It shelved those plans in 2022 as equity markets nosedived, but remained focused on an eventual IPO.
EToro was founded in 2007 by brothers Yoni and Ronen Assia and David Ring. The company makes money through trading-related fees and nontrading activities such as withdrawals. Net income increased almost thirteenfold last year to $192.4 million from $15.3 million in 2023.
The company has steadily built a growing business in cryptocurrencies. Revenue from crypto assets more than tripled to upward of $12 million in 2024, and one-quarter of its net trading contribution stemmed from crypto last year. That is up from 10% in 2023.
EToro said that for the first quarter, it expects crypto assets to account for 37% of its commission from trading activities, down from 43% a year earlier.
Spark Capital is the company’s biggest outside investor, with 14% control after the offering, followed by BRM Group at 8.7%. CEO Yoni Assia controls 9.3%.
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