How much technical talent is there? A systematic estimate of the ML research pool among 3 million consultants

TL;DR

This paper systematically estimates the size of the ML research talent pool within consulting firms, revealing a substantial and largely untapped resource of technically skilled professionals in the industry.

Contribution

It introduces a novel methodology combining internet searches, LLM classifiers, and statistical modeling to estimate ML research talent across thousands of firms.

Findings

Estimated 1121 highly technical ML researchers per firm on median

Found 403 firms offering broad ML consulting services

No AI model passed the late 2025 work trial for technical AI safety

Abstract

We identify a substantial pool of technically competent ML research talent (in the low thousands) in companies which offer consulting in machine learning. We systematically searched the internet, global business databases, and conference/paper affiliations for ML consulting firms. Employee LinkedIn resumes were then scored by keyword filters and large-language-model (LLM) classifiers; these signals were combined in a bootstrap probit model to estimate technical ML research talent per firm. A subset of companies also completed a 3-day research and engineering work trial. We screened 2121 organizations and found 403 offering broad ML consulting. Our 50th percentile aggregate estimate of 'highly technical' ML research talent across these organizations was 1121 (80% CI: 252-3165) -- i.e. twice as many as all alumni of the MATS training program. For our work trial 97 companies were approached, 20 applied, 8 were invited to participate, and 5 of 8 received at least a conditional recommendation for technical AI safety work. As of late 2025, no AI model was able to pass the work trial.