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Member of Technical Staff at -performing AI forecasting startup major seed funding
Job in
Greater London, London, Greater London, W1B, England, UK
Listed on 2026-06-12
Listing for:
Jack & Jill
Full Time
position Listed on 2026-06-12
Job specializations:
-
IT/Tech
AI Engineer (Applied/Software), Data Scientist -
Research/Development
Data Scientist
Job Description & How to Apply Below
Location: Greater London
Job Title
Member of Technical Staff
Company DescriptionTop-performing AI forecasting startup backed by a recent major seed round and $4M pre‑seed
Job DescriptionYou will join a world-class technical team to solve judgmental forecasting using LLM agents. By building deep research agents and experimenting with probability distribution tools, you will improve decision‑making in geopolitics and economics. This role involves rapid experimentation cycles and pushing the frontier of AI accuracy alongside veterans from Deep Mind and Citadel.
LocationLondon, UK
Why this role is remarkable- Work with an elite technical team from Google Deep Mind, Citadel, Palantir, and Oxford VGG, tackling one of the most intellectually challenging problems in AI.
- Join a project recognized by Polymarket as the best‑performing AI forecasting system, recently placing 4th out of 500+ participants in the prestigious Metaculus Cup.
- Impact a mission‑driven product featured in The Atlantic and The Guardian that aims to radically improve global decision‑making through superior predictive reasoning.
- Design and implement LLM agent scaffolding to improve forecasting accuracy across geopolitics, business, and technology sectors.
- Develop new benchmarks and tools that allow LLMs to express complex probability distributions and conduct deep autonomous research.
- Conduct short, high‑impact experiments to analyze prediction failures and iterate on the system's reasoning capabilities within one‑week project cycles.
- Possesses a strong work ethic and exceptional coding ability with a proven track record of delivering high‑quality research or technical projects.
- Demonstrates comfort with statistics and probability, ideally with experience in quantitative finance, AI labs, or advanced academic research on LLMs.
- Shows evidence of exceptional achievement in any domain and is eager to work in‑person 5 days per week in a high‑intensity London office.
Not Disclosed
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