Visible data through the first half of 2026 show that among 29,317 current-employee profiles at 25 top quant firms, 367 people now at frontier AI labs carry quant-firm experience (233 of them in full-time quant roles), versus 90 the other way.
The figures below reflect what is visible in the Metix AI database (data through the first half of 2026). The population = talent currently employed at 25 top quant firms and based in the US / UK / Singapore / Hong Kong / Netherlands, plus the two-way flow between quant and the frontier AI labs.
On the visible data, people now at a frontier AI lab who carry quant-firm experience number 367 (of whom 233 held full-time quant roles rather than student internships); the reverse flow (now in quant, with AI-lab experience) is just 90. Even counting full-time quant roles only, the net direction is still about 2.6:1 (4.1:1 once internships are included). Quant is a net supplier of talent to the AI labs, not the other way around — putting Bloomberg's anecdotal coverage of AI-lab rooftop parties aimed at hiring quants onto full-population direction and scale for the first time.
Broken out by current lab: OpenAI leads with 159 ex-quant hires, followed by Anthropic 94, Google DeepMind 78, xAI 32. This tracks OpenAI's and Anthropic's intensive 2025 quant-focused recruiting across Manhattan and London. The biggest exporters are Citadel (84), Jane Street (80) and Two Sigma (47).
Quant firms lock people in with multi-year deferred compensation and 3-4-year non-competes / garden leave; with the FTC's nationwide non-compete ban struck down in 2024 and Florida's CHOICE Act allowing 4-year non-competes, the lock-in has only tightened. But the key structural crack is this:AI labs are not treated as quant "competitors", so a quant can join OpenAI directly during garden leave, and the AI labs have become the default place to sit out a non-compete. The tenure data (Section 5) uses this to pinpoint the high-mobility windows.
The following is verified point by point against public sources from 2024-2026 (full sources in the research memo), keeping only facts that affect talent decisions. Dollar figures are as reported and are mostly individual cases.
Bloomberg (2025-08-08) reported that OpenAI, Perplexity and others are recruiting quants directly from banks and quant firms; Anthropic threw a roughly 150-person quant cocktail party on a Lower East Side Manhattan rooftop in 2025-06 and ran a dedicated London session in 2025-8 (August). Named, publicly verified moves: Jane Street → Anthropic (Aron Thomas, James Chen and others), Citadel / Citadel Securities → OpenAI (Zeyuan Shang, Andrey Grinshpun and others, many joining during garden leave), Jane Street → OpenAI (Mark Chen, now OpenAI's Chief Research Officer, CRO).
Entry-level quant base pay is reported "as high as $300K" (excluding bonus); HFT shops even re-hire interns at up to $425K to defend the pipeline. On the AI-lab side: median total comp for an OpenAI researcher is around $1 million (L4 base $297K + $474K in stock), and offers to a few quants with a few years' experience reportedly reach $3 million; OpenAI's 2025 average stock comp per head was roughly $1.5 million. The structural shift is that the labs can now match base pay and replace the quant bonus with equity upside, so candidates "no longer have to take a pay cut."
Low-latency systems, large-scale GPU / inference optimization, and a reinforcement-learning mindset that shares its roots with market microstructure are exactly the skills the AI labs are short of. At the same time the quant firms are building AI themselves: XTX has stood up a cluster of more than 25,000 GPUs, HRT founded HAIL to "build foundation models for markets," Two Sigma's effort is led by ex-Google's Mike Schuster, and Citadel uses RL to optimize trading. Ken Griffin conceded in 2025 that "this time AI is real" — and that he is fighting over the same quantitative talent as AI.
The FTC's nationwide non-compete ban was struck down nationwide by the courts in 2024-08; Florida's CHOICE Act took effect in 2025-07, allowing 4-year non-competes / garden leave; Citadel pushes 4-year terms, SIG 3 years, and buy-side sit-outs are typically 12 months, stretching to 24-36 months. The real cost is forfeited deferred compensation (unvested equity is the cost of leaving). But because the AI labs are not seen as quant "competitors," a quant can legally join a lab during a non-compete / garden leave — the legal loophole that lets this two-way flow take shape.
Population = 29,317 current quant-firm employees (including a 11,632-person technical pool: quant research / quant dev / ML research / HFT systems / data).
Reading: Citadel (5,798), Point72 (2,337) and Jane Street (2,112) lead on size. Note the wide variation in profile-maintenance rates: quant firms generally have strict NDAs and low LinkedIn upkeep, so absolute counts are a visible floor; small prop shops (such as PDT and Quadrature) naturally have few profiles.
Reading: quant dev (7,056) and quant research (3,320) make up the bulk of the technical pool — and the two categories the AI labs want most (research thinking + large-scale systems engineering). Only 176 are explicitly tagged as ML / AI research; quant firms' ML capability is mostly hidden under "quant researcher / dev" titles, so titles understate true AI ability and assessment has to come back to portfolios and competition / publication backgrounds.
Reading: the US dominates at 19,848 (the two quant hubs of New York + Chicago), the UK 6,108 (London — XTX / Qube / Marshall Wace / G-Research); in Asia, Singapore 1,198 + Hong Kong 1,104 are the growth poles (Jane Street, HRT and Citadel Securities are expanding), and the Netherlands 1,059 (Optiver / IMC in Amsterdam).
Reading: founders / executives 2,582 and directors / leads 2,067 form the reachable senior layer; the 4,451 juniors / interns reflect quant's "campus hiring + intern-to-full-time" pyramid — also the layer where the AI labs compete most fiercely at entry level (HFT defends with $425K intern re-hire offers).
This is the heart of the report. On the visible data, quant → AI lab is 367 (including student internships; 233 in full-time quant roles), and AI lab → quant is 90, a net direction of about 4.1:1 (2.6:1 counting full-time roles only). Below we unpack direction, source and destination point by point.
Reading: the thickest corridor is Citadel → OpenAI (49). OpenAI and Anthropic are the two big collectors, Citadel (incl. Securities) and Jane Street the two big sources — and the very firms most often named as "net exporters" in public coverage.
Reading: OpenAI (159) leads, with Anthropic (94) and Google DeepMind (78) next. OpenAI's and Anthropic's high intake maps directly onto their intensive 2025 quant recruiting (rooftop parties, garden-leave hires).
Reading: Citadel (84), Jane Street (80) and Two Sigma (47) are the top three sources. This is consistent with their scale, research culture (Jane Street's ML track, Two Sigma's generative-AI team) and the degree to which the labs target them.
Reading: Citadel and Jane Street sit top-right (large, high outflow) as the main sources of the flow; Two Sigma's outflow intensity runs high relative to its size (its research culture is closer to the AI labs').
Reading: the reverse flow is just 90 people — about 1/4.1 of the forward flow — so quant is a net exporter overall. Most reverse-movers come from Google DeepMind (42, the earliest-founded, with the most alumni), a few from OpenAI (27). The motive is usually pay certainty and "de-bubbling," not the mainstream.
Jane Street → Anthropic: Aron Thomas, James Chen, Charles Guo, Kerrick Staley (mostly MTS / research track).Citadel / Citadel Securities → OpenAI: Zeyuan Shang, Andrey Grinshpun, Eugene Tang (many joining during a non-compete / garden leave).Jane Street → OpenAI: Mark Chen (now OpenAI's Chief Research Officer, CRO).Reverse (AI → quant side): Leopold Aschenbrenner left OpenAI to found the Situational Awareness fund (an AI-research background turned to AI-themed investing). These named cases align with the report's full-population direction: talent flows mainly from quant to the AI labs.
Sources: Bloomberg 2025-08-08, eFinancialCareers, and each company's public information (see the research memo for detail). For named cases, current roles are per public sources.
Quant locks people in with multi-year deferred comp + non-competes / garden leave. Tenure structure lets you back out the "vesting cliff / non-compete expiry" outreach windows — the timetable headhunters and AI-lab recruiting should watch most closely.
Reading: 7,002 people have 2-4 years' tenure, landing squarely in the zone where most firms hit a large deferred-comp vesting cliff / the initial non-compete nears expiry — the most mobile, highest-priority group to approach. The <1-year cohort (7,288) is mostly in the honeymoon phase with the freshest, tightest non-competes; 5+ years (6,504) is the settled senior layer, hard to reach but high-value.
| Mechanism | Typical terms (as reported) | What it means for outreach |
|---|---|---|
| Deferred comp / unvested equity | Vests over multiple years | The 3-6 months before a vesting cliff is the leading edge of the window; the unvested amount = the real cost of moving |
| Non-compete / garden leave | Citadel up to 4 years · SIG 3 years · buy-side 12-36 months | The run-up to expiry is the window; AI labs, not being "competitors," can be joined during garden leave |
| Non-compete legal environment | FTC nationwide ban struck down in 2024; Florida 4-year non-compete | Lock-in is stronger but also more predictable; approach on the expiry schedule |
| Entry-level defense | HFT re-hires interns at up to $425K | The entry level is exactly where the labs compete hardest and firms defend most expensively |
A curated set of 19 people across three groups, drawn from the quant → AI-lab movers and selected for full-time quant experience (not student internships), seniority and corridor representativeness. Profile facts come from the Metix AI database; those marked "publicly verified" are public figures or Bloomberg-named cases confirmed against public sources. Names are masked by default in the public version.
Quant and the AI labs fight over the same people but bid with different structures: quant offers certain cash (base + a large bonus + deferral), the AI labs offer matched base + equity upside. Figures are as reported for 2025-2026 and are mostly individual cases.
| Group | Pay range (as reported) | Notes |
|---|---|---|
| Entry-level quant (base) | Up to $300K | Bloomberg; Jane Street / Five Rings researcher base ~$300K (per H1B filings) |
| Top summer internship | ~$25K/month; re-hire offers up to $425K | HFT defends the entry pipeline with high pay (OpenAI is closing in) |
| OpenAI researcher (median total comp) | ~$1 million (L4 base $297K + $474K stock) | levels.fyi; L5 median about $1.47 million |
| OpenAI's offer to a senior quant | Reportedly up to $3 million | Single source, individual case, cite with caution |
| Anthropic SWE (levels) | ~$560K-$780K; senior researchers above $1 million | Includes tender liquidity |
| Meta Superintelligence (star case) | Reported into the ~$100 million range | Extreme case, RSU structure, cite with caution |
Hiring a quant used to mean asking them to "take a pay cut for the mission"; the 2025 change is that the labs can nowmatch the base and replace the quant bonus with equity upside, so candidates "no longer have to take a pay cut" (in Noam Brown's words). Layer on AI's narrative and research freedom and the balance tilts toward the labs — the comp-side explanation for this flow's 4.1:1 net outflow.
① Headhunters: quant → AI candidates are highly sensitive to "cash certainty vs equity upside," so open by spelling out the stock structure and liquidity (tender); ② quant HR: defense rests on deferred vesting + non-competes + high entry pay, but must accept that base has been matched; ③ AI-lab recruiting: use the three-piece combo of "legal hire during garden leave + matched base + upside" to target quants at 2-4 years' tenure precisely.
Sources: Bloomberg, eFinancialCareers, levels.fyi, Fortune, and company public information (retrieved 2025-2026). See the research memo for detail; treat items marked "individual case / single source" with caution.
Turning the flow map into action: headhunters watch the outreach windows and named corridors, quant HR watches defense, AI-lab recruiting watches precision attraction.
① Focus on the 2-4-year-tenure cohort with a vesting cliff approaching (Section 5) — the highest success rate; ② proven corridors (Citadel / Jane Street → OpenAI / Anthropic) carry low candidate resistance; ③ reach proven-corridor candidates via alumni + competition circles for a high hit rate; ④ with quant profile-maintenance low, this report's full-population picture + current-status data is itself scarce talent intelligence.
① Use this report's "exporter ranking" (Section 4.3) to position yourself against the biggest-bleeding peers; ② defend by watching 2-4-year tenure technical roles (the most likely to be approached by the labs); ③ accept that the labs have matched base, so defense rests on deferred vesting + non-compete scheduling + high entry pay; ④ reverse intake (AI → quant, just 90 people) is a small but real opportunity, mainly from DeepMind alumni.
① Attract quants at 2-4 years' tenure with the three-piece combo of "legal hire during garden leave + matched base + equity upside"; ② prioritize HFT-systems / low-latency + RL backgrounds (the most transferable skills); ③ replicate OpenAI's and Anthropic's "firm-by-firm dedicated event" playbook (the rooftop-party model); ④ screen precisely by university (Tsinghua/Peking / USTC / MIT / CMU) + competition background.
All of this report's search, profiling and two-way-flow analysis was done by Metix AI. We can produce a custom talent-flow analysis for any firm on the same basis: full long-list export, filtering by tenure / non-compete window, reconstruction of named corridors, email unlock and multi-channel outreach — billed on a "pay only for qualified interviews" model. No interview, no charge.
860 million+ global talent profiles29,317-person quant pool + a 367-person flow listTenure / non-compete window targetingPay only for qualified interviews25 top quant firms (hedge funds + prop market makers), geography = profiles resident in the US / UK / Singapore / Hong Kong / Netherlands. Quant pool = currently employed, with a current employer that matches a target firm after a financial-services filter (Financial Services / Capital Markets, etc.). Frontier AI labs = OpenAI / Anthropic / Google DeepMind / xAI / Mistral / Meta AI (FAIR).
Quant → AI lab = currently employed at a frontier AI lab and with a target quant firm in their history (financial-services-filtered). AI lab → quant = currently employed at a quant firm and with a frontier AI lab in their history. One person can count on multiple source corridors (Sankey edges).
Roles are classified by title / headline (quant research / dev / trading / ML research / HFT systems / data / executive / functional); the technical pool = research + dev + ML + HFT + data. Tenure = months in the current role at the firm. All are probabilistic inferences, and titles understate the true ML capability inside quant firms.
| Firm | Current pool | Technical pool | →AI Lab |
|---|---|---|---|
| Citadel | 5,798 | 2,276 | 84 |
| Point72 | 2,337 | 684 | 8 |
| Jane Street | 2,112 | 753 | 80 |
| Susquehanna (SIG) | 2,085 | 777 | 24 |
| Two Sigma | 1,700 | 827 | 47 |
| Optiver | 1,572 | 597 | 15 |
| DRW | 1,544 | 607 | 9 |
| Jump Trading | 1,335 | 819 | 29 |
| IMC Trading | 1,323 | 562 | 15 |
| Squarepoint | 1,284 | 800 | 4 |
| Qube Research | 1,182 | 367 | 1 |
| D. E. Shaw | 1,113 | 174 | 23 |
| Hudson River Trading | 1,004 | 594 | 37 |
| G-Research | 818 | 498 | 9 |
| Virtu Financial | 724 | 195 | 3 |
| Tower Research Capital | 634 | 245 | 15 |
| Marshall Wace | 588 | 200 | 1 |
| AQR Capital | 552 | 75 | 9 |
| Akuna Capital | 309 | 169 | 9 |
| Millennium | 295 | 88 | 1 |
| Five Rings | 243 | 111 | 15 |
| Renaissance Technologies | 211 | 46 | 0 |
| XTX Markets | 198 | 74 | 0 |
| PDT Partners | 185 | 10 | 2 |
| Quadrature | 171 | 84 | 1 |
① Coverage / maintenance rate: quant firms have strict NDAs and low LinkedIn upkeep (sample-measured: name / work history 100%, education about 58%, languages about 24%), so absolute counts are a visible floor; cross-firm comparison relies primarily on shares and structure, with absolute counts secondary.
② Entity ambiguity: Citadel covers both the hedge fund and Citadel Securities; same-named companies are excluded by the financial-services filter (e.g. Citadel Broadcasting / colleges have been removed).
③ The flow is inferred from work histories: based on the sequence of public employment records, with no reason for leaving; for named cases, current roles are per public sources and should be re-confirmed before use.
④ Research memos: two research memos with all source URLs (industry landscape / talent ecosystem) are delivered in the same directory as this report.