Quant firms, AI labs push entry pay past $1 million for math talent

Quant trading firms and AI labs now pay top math graduates more than $1 million a year to secure their skills.

The competition between quantitative trading firms and artificial-intelligence companies for top math and computer-science graduates has pushed entry-level compensation past $1 million, up from $350,000 to $500,000 just a few years ago.

"The delineation is pre-OpenAI and post-OpenAI — that's when you saw competition really take off," Matt Stabile, founder of recruitment firm Stabile Search, said.

Standard entry-level packages at elite quant firms range from $350,000 to $500,000, but return offers for top summer interns have reached $700,000, and rare starting deals have hit $1.5 million, according to Kevin Cassata, founder of executive-search firm Karbon Agency. Summer internships at firms such as Optiver routinely pay more than $30,000 a month. The bidding has intensified as AI labs including OpenAI and Anthropic compete for the same pool of graduates with expertise in machine learning and large language models.

The talent war threatens to drain academia of future researchers. At Oxford University's Mathematical Institute, a majority of doctoral students begin their studies aiming for academic careers, but summer internships at quant firms routinely alter those plans, according to Alvaro Cartea, a math professor and director of the Oxford-Man Institute. His students who enter quant earn between $300,000 and $1 million, with those skilled in large language modeling receiving offers at the higher end.

How the AI Boom Reshaped Wall Street Hiring

The skills required to train large language models have always overlapped with quantitative finance, but the connection has deepened as trading firms have pivoted toward machine learning and AI to power their trades. A single star employee's algorithm can generate hundreds of millions of dollars — a factor that has helped firms such as Jane Street produce outsize profits. In the first quarter of 2026, Jane Street made a record profit of $10.3 billion, nearly double the earnings of Goldman Sachs and Morgan Stanley combined, despite having a fraction of the employees.

That earning power helps top shops compete with tech titans. Andrew Lai, who earned a computer-science doctorate at the Massachusetts Institute of Technology specializing in machine learning, interned at Microsoft and Nvidia before trying Optiver. He chose quant because it let him see research results faster and offered higher pay than tech. About a third of his PhD lab mates went into quant, with roughly an equal share going into tech, he said.

Firms Lock Down Talent Earlier

To prevent star interns from reaching the open market, trading firms are expanding summer internship programs to lock down students a year or more before they graduate. Optiver currently fills 70 percent of its graduate hires through internships and plans to eventually fill all entry-level roles this way. The firm sponsors chess grandmasters and hosts an annual tournament, while rival Qube Research & Technologies runs an intracompany Rubik's Cube competition — all part of leaning into the nerdy culture that appeals to this hyperintellectual crowd.

Laura Zhang, a math and computer-science student at MIT, first learned about quant firms at a high-school math competition sponsored by one of the companies. Now she watches those same firms compete to hire her classmates, flying students to offices for early-career programs and visiting campuses regularly.

The Shift From AI Labs Back to Quant

When Daniel Wu graduated from Stanford with a degree in computer science in 2021, he interviewed at AI labs before joining a quant firm as a researcher. "Comp was a big factor," he said. "At the time, quant firms were making the most competitive offer financially." Now, he said, most of his peers opt for offers from Anthropic or OpenAI, drawn by the prospect of shaping the hottest new technology.

The dynamic creates a two-way pressure. Quant firms must keep raising pay to retain talent that AI labs covet, while AI labs must compete with Wall Street's profit margins. For investors, the talent cost represents a structural expense that could pressure margins at both types of firms. OpenAI and Anthropic face the additional challenge of competing against firms where a single algorithm can generate hundreds of millions in profit, making million-dollar salaries a rounding error.

This article is for informational purposes only and does not constitute investment advice.