Member of Technical Staff
You will develop and refine LLM agents, working with agent scaffolding and internal benchmarks. Mantic builds AI systems that outperform human superforecasters in predicting geopolitical, economic, and technological events.
Free Tailor for ATS: 10/10 runs left
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Job Title
Member of Technical Staff
Salary
Not Disclosed + Equity
Company Description
Mantic is a London-based AI startup that recently raised a $23M seed round to solve judgmental forecasting. Backed by a world-class team from DeepMind and Citadel, Mantic builds AI systems that outperform human superforecasters in predicting complex geopolitical, economic, and technological events.
Job Description
You will push the frontier of forecasting accuracy by developing and refining LLM agents. Working in short, high-impact cycles, you'll improve agent scaffolding, conduct research experiments, and build internal benchmarks. This role focuses on enabling LLMs to express complex probability distributions and reason through ambiguous, real-world data to drive radical improvements in global decision-making.
Location
London, UK
Why this role is remarkable
Work at the frontier of AI forecasting with a system already recognized by Polymarket as the best-performing AI in the field.
Collaborate with an elite technical team featuring alumni from Google DeepMind, Citadel, Goldman Sachs, and top-tier academic institutions like Oxford and Cambridge.
Join a well-funded mission with a recently closed $23M seed round following a $4M pre-seed, providing significant runway and growth potential.
What You Will Do
Design and implement advanced scaffolding for LLM agents to improve reasoning and research capabilities.
Create and maintain internal benchmarks to evaluate forecasting accuracy across diverse domains like geopolitics and economics.
Analyze model failures and bad predictions to iteratively refine how AI systems express complex probability distributions.
The ideal candidate
Possesses exceptional coding ability and a strong background in conducting technical research projects, particularly with LLM agent frameworks.
Demonstrates deep comfort with statistics and the ability to apply quantitative reasoning to uncertain, judgmental forecasting problems.
Brings a high-performance work ethic and evidence of exceptional achievement, likely proven through experience in AI labs, quant finance, or academic research.
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