Figure AI, a leading humanoid robotics startup in Silicon Valley, has revealed staggering statistics about its hiring process that highlight the intense competition in the AI and robotics job market. CEO Brett Adcock disclosed on X that the company received 176,000 job applications over the past three years since its 2022 founding, yet hired only 425 people — resulting in an acceptance rate of approximately 0.24%.
This hiring rate is dramatically lower than even the most selective Ivy League universities. For context, Caltech, which has the lowest college acceptance rate in the US, admits 3% of applicants according to US News & World Report — more than 12 times higher than Figure AI’s rate. Even if the applications were distributed evenly across the three years (roughly 59,000 annually), the acceptance rate would still be extraordinarily low.
Adcock characterized most submissions as “slop” and described the review process as incredibly time-consuming. “We go through these one by one like a monkey — it’s incredibly time consuming,” he wrote. The CEO noted that even with applicant tracking systems (ATS), the software employers use to filter résumés, the process remains laborious. “In the ATS it takes at least 20 seconds of button clicks per submission even if it’s garbage,” he explained.
Figure AI’s situation exemplifies the convergence of two major job market trends. First, modern job seekers are applying to unprecedented numbers of positions — data from Greenhouse, a leading ATS platform, shows the average job opening now receives 242 applications. Second, the company operates in one of tech’s hottest sectors: robotics and artificial intelligence, where competition for talent is fierce.
The AI talent war has intensified dramatically, with companies like Meta and OpenAI offering seven- to nine-figure compensation packages to attract superstar AI researchers. Even startups are competing aggressively, offering higher equity stakes, co-founding titles, and more research time.
Figure AI has established itself as a leader in humanoid robotics, recently completing a Series C funding round that raised over $1 billion from investors including Parkway Venture Capital, Brookfield Asset Management, and Nvidia, achieving a $39 billion valuation. Adcock suggested he may need to develop an AI model specifically to handle the résumé screening process more efficiently.
Key Quotes
Just checked, 176,000 job applications at Figure the last 3 years. We’ve hired ~425 people.
Figure AI CEO Brett Adcock revealed these statistics on X, highlighting the company’s extraordinarily selective hiring process with a 0.24% acceptance rate — lower than any Ivy League university.
We go through these one by one like a monkey — it’s incredibly time consuming.
Adcock described the laborious manual review process his team undertakes, emphasizing that even advanced applicant tracking systems cannot adequately handle the volume of applications the AI startup receives.
In the ATS it takes at least 20 seconds of button clicks per submission even if it’s garbage.
The CEO explained the limitations of current applicant tracking system technology, noting that even obviously unsuitable applications require significant time to process, creating a massive operational burden.
Need a model to do this for us better, maybe I’ll work on one.
Adcock suggested developing an AI solution to handle résumé screening more efficiently, highlighting the irony that an AI company is struggling with a problem that artificial intelligence could potentially solve.
Our Take
Figure AI’s hiring statistics reveal a fundamental tension in the AI industry: companies are simultaneously desperate for talent yet overwhelmed by applicants. The 0.24% acceptance rate isn’t just about selectivity — it reflects how AI and robotics have captured the imagination of job seekers worldwide, creating unprecedented competition.
What’s particularly striking is that a company at the forefront of AI technology is struggling with a problem that seems tailor-made for AI solutions. This suggests current HR technology and ATS platforms are inadequate for the scale and complexity of modern hiring, especially in hot sectors like AI.
The broader implication is concerning: if even qualified candidates face near-impossible odds, the industry risks creating artificial barriers that could slow innovation and exclude diverse talent. Figure AI’s experience may force the industry to rethink recruitment entirely, potentially accelerating the development of more sophisticated AI-powered hiring tools that can genuinely assess candidate quality rather than just filtering keywords.
Why This Matters
This story reveals critical insights about the AI talent landscape and the extreme competitiveness of the robotics sector. Figure AI’s microscopic acceptance rate demonstrates how AI and robotics companies have become the most sought-after employers in tech, attracting overwhelming interest from job seekers worldwide.
The situation highlights a paradox in the AI job market: while companies desperately need AI talent and are willing to pay premium salaries, they’re simultaneously drowning in applications, making it nearly impossible for qualified candidates to stand out. This creates significant inefficiencies in hiring processes that even advanced ATS software cannot solve.
The irony that an AI company is struggling with a problem that AI could potentially solve — résumé screening — underscores both the limitations of current AI tools and the opportunity for innovation in HR technology. Adcock’s suggestion to build a model for this purpose could represent the next evolution in AI-powered recruitment.
For the broader tech industry, this signals that competition for positions at leading AI companies will only intensify, potentially creating barriers to entry even for highly qualified candidates and raising questions about how companies can efficiently identify top talent amid the noise.