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arXiv · 2603.00062

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

Maximilian Schons·Red Bermejo·Florian Aldehoff-Zeidler·Niccolò Zanichelli·Oliver Evans·Gavin Leech·Samuel Härgestam
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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.

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Maximilian Schons, Red Bermejo, Florian Aldehoff-Zeidler, Niccolò Zanichelli, Oliver Evans, Gavin Leech, Samuel Härgestam. 2026-02-10. How much technical talent is there? A systematic estimate of the ML research pool among 3 million consultants. https://arxiv.org/abs/2603.00062

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