Executive Summary

01 Listed headcount ≠ R&D scale

Metix AI global talent pool, data through mid-2026. We count each of the seven companies' listed members and isolate the current "engineering + research + creative design" core (the builders). All figures are aggregate, with no personal information.

518 / 1,687

builders / listed members

Engineering 60% · Research 21% · Creative 13% · Founders 7%

70%

joined in the past two years

Most are scaling fast, leaving a wide mobility window

13.7%

PhD share among builders

≈ OpenAI 14.4% / Anthropic 13.7%

5

Talent geographies

US labs / Israel / Kazakhstan / UK-Europe / US-Canada

① Listed headcount ≠ R&D scale

Of 1,687 listed members, only 518 are builders (about a third). The rest are creator communities and sales. To benchmark team size, separate these three layers first — and watch out for inflated "community" counts, especially on consumer products.

② Different structures: research shops vs. product shops

Across the field it's 60% engineering, 21% research, 13% creative. But Luma is 55% research and Higgsfield is 80% engineering — "build-your-own-model" and "application-layer product" map to completely different hiring profiles.

③ Big Tech dominates, film VFX barely registers

The biggest feeders are Google / Meta / Amazon. Film-VFX backgrounds are under 1%, and "Hollywood crossover" is the exception. The real video talent comes from machine learning, Big Tech engineering, and self-driving, defense intelligence, and search engines.

④ Five talent geographies, all expanding

US labs, Israel, Kazakhstan, UK-Europe, US-Canada — five disconnected markets. 70% joined in the past two years and only 6.8% are new grads: this is pure lateral hiring.

Methodology. We count only the seven pure-play video / generative-media companies; OpenAI Sora and Google Veo sit inside their parent companies and can't be isolated, so they appear only as feeders and background, not in the totals. All figures are independently verified. The same x-ray can be generated on demand for any target company.

Team Composition

02 How big the R&D core is, and who's in it

Listed headcount isn't R&D headcount. Builders are only about a third — the chart below compares each company's absolute builder count against its total listed members.

Company Builder Distribution

Who are the "creator communities"? These are members of consumer products' Creative Partner / Ambassador programs. They often list several products at once as their "current role" (we've seen one person tagged to more than ten), and they're ecosystem promoters, not employees — at Pika and Higgsfield this group makes up 30–40% of the listed count. Break them out separately when benchmarking a team.

What the builders are made of

Split by function, you can tell at a glance whether a company is research-driven or product-driven: Luma is more than half research, Higgsfield is 80% engineering. Creative / design appears everywhere (13% across the field), but almost none of it comes from film VFX.

Function Breakdown

Each company's builders by function (totals to 100%). Source: Metix AI

Where The Talent Comes From

03 Where the talent comes from: Big Tech leads, film VFX barely shows up

Builders' prior employers, deduplicated and ranked — the top 11 feeders, dominated by Big Tech.

Bar length = number of builders who once worked there (deduplicated, by person; Google's 39 = 100%). Source: Metix AI

Looking only at "video-relevant" feeders, self-driving 3D vision, defense intelligence, and search engines come out on top, while film VFX is essentially zero.

VFX career-switchers? Even on the broadest definition, among the 518 builders, film-VFX backgrounds are under 1%, and they surface only sporadically at Runway / Luma. The R&D core is built from machine learning and Big Tech engineering, and even the creative / design hires come mostly from product design rather than the film pipeline.

Note. The "Israeli defense intelligence ≈24" is almost entirely concentrated in one company, Decart (24 of its 38 builders) — that reflects "Decart is an Israeli-rooted company," not a sector-wide pattern; likewise, Yandex is concentrated at Higgsfield. See the next section for details.

Five Talent Geographies

04 One sector, five disconnected markets

Split by location, the seven companies simply aren't hiring in the same market. The chart below shows each company's geographic distribution, and the cards give the underlying talent profile and hiring advice.

Geographic Distribution

Market Profiles

① US labs · Luma / Runway

83 / 87 builders

26.5% · 12.6% PhD rate

71% · 62% in the US

The model core. Feeders are Meta / Google / NVIDIA, plus a hidden pipeline — self-driving 3D vision (7 of Luma's people came from Waymo / Cruise / NVIDIA). Luma is 55% research and 26.5% PhDs, the most research-leaning of all.

② Israel · Decart

38 builders

63% defense-intelligence background

76% in Israel

The leanest team: 91 listed members, only 8 of them community tags. 24 of its 38 builders have Unit 8200 / IDF backgrounds, layered with Technion. A textbook Israeli deep-tech profile.

③ Kazakhstan · Higgsfield

50 builders

80% engineering roles

68% in Kazakhstan

The team is in Kazakhstan, not Silicon Valley. Feeders are Yandex plus local incubators (nFactorial, Aviata). Engineering-driven and the youngest of the group (median tenure 11 months), with a search / growth foundation.

④ US / Canada · HeyGen

93 builders

67% + 20% in the US / Canada

ByteDance 6 · Huawei 4 China pipeline

The engineering core sits in the US and Canada, not China. But there's a clear China Big-Tech pipeline: ex-Snap 9 + ByteDance 6 + Huawei 4. A product-engineering shape, with a 3.2% PhD rate.

⑤ UK / Europe · Synthesia

150 builders

23 months median tenure

92% in the UK / Europe

The most senior and the most B2B-SaaS-like. Feeders are Google / Amazon / Microsoft plus UCL, with 92% in the UK and Europe. Its large listed count comes from a 265-person sales team, not a community.

＋ San Francisco squad · Pika

17 builders

35% Creative / design

76% in the US

A tiny elite team (17 people; percentages are indicative only). The highest creative / design share of the seven, with feeders including Google and ByteDance, and founders out of Stanford / Meta AI.

Credentials & Hiring Pace

05 Education and hiring cadence

The education mix confirms the research-vs-product divide: Luma has the most PhDs, Higgsfield is mostly bachelor's degrees. ("Not listed" = no education info in public records, which doesn't mean no degree.)

Hiring cadence: 70% joined in the past two years, only 6.8% new grads, and a median career length of 7–14 years — overwhelmingly lateral hiring. The chart below shows each company's hires in the past 12 months.

External benchmark. The builder PhD rate (among those with a degree) is 13.7%, on par with OpenAI (14.4%) and Anthropic (13.7%). What drags down the overall listed PhD rate is community and sales, not low-caliber engineering.

The China pipeline is in the feeders, not the locations. By employer alone: ByteDance 15 + Huawei 10 + Tencent, flowing mainly to HeyGen and Luma.

How To Use This

06 How HR / recruiters / VCs can use this

HR: benchmark on an R&D basis

When benchmarking team size, strip out creator communities and sales first — a competitor's "hundred-person team" may have real R&D of only a third. By profile: for cinematic generation, hire from Big Tech plus self-driving CV; for enterprise digital humans, hire from B2B SaaS.

Recruiters: follow the feeders

Almost no new grads, and 70% joined in the past two years — a large pool of talent is in its mobility window right now. The biggest feeders are Big Tech; the underrated ones are self-driving 3D vision, and regionally, Israel's Unit 8200 and Yandex.

VCs: use talent structure for diligence

Function mix, PhD rate, and feeders read straight off whether a company is "build-your-own-model" or "application-layer." The "listed headcount" must be split into three layers — how much community and sales is mixed in determines the real R&D capacity.

FAQ

Questions this report answers

How many builders sit inside the seven AI-video companies? Seven AI video companies, 1,687 listed members — but only 518 are actually building. They come from Big Tech and self-driving — film VFX is under 1%.

How are “builders” defined versus listed members? Metix AI global talent pool, data through mid-2026. We count each of the seven companies' listed members and isolate the current "engineering + research + creative design" core (the builders). All figures are aggregate, with no personal information.

How should this report be cited? Metix AI Talent Intelligence, 2026-06-22. AI Video Generation Talent Map 2026 | Metix AI. https://metix.ai/reports/mapping/ai-video-generation-talent-2026

Want the full list for one company, or your own target company instead?

Population cleanup, function mix, feeders, and geography can all be generated on demand for any single AI video / generative-media company, and connected to reachable candidates.

Note: This report is based on the Metix AI global talent pool, counting the listed members of seven AI video / generative-media companies (taking current members, then isolating "builders" by engineering + research + creative design roles), with data through roughly mid-2026. Every figure is an aggregate result over the visible sample and is indicative only; companies with smaller samples (such as Pika, with just 17 builders) should be read with caution; the report shows no individual names, contact details, or sensitive attributes.