Web Researcher – AI Benchmarking
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Job Description
Web Researcher designing difficult open-web problems for frontier AI browsing agents. Building evidence trails and reproducible benchmarks from verifiable facts.
Responsibilities:
- Design challenging open-web research problems for evaluating advanced AI browsing agents.
- Start from objectively verifiable facts and construct questions that make those facts difficult to discover.
- Build multi-step clue structures involving dates, people, places, organizations, works, events, records, and quantities.
- Ensure every clue is independently verifiable and subject to clear constraints.
- Research across government databases, institutional sources, archives, registries, and PDF documents.
- Produce complete evidence trails citing exact pages, tables, sections, or records.
- Record validation searches and document what obvious search approaches return.
- Test whether research questions remain difficult across multiple search attempts.
- Refine questions to eliminate ambiguity while preserving difficulty.
- Deliver structured, reproducible research documentation.
Requirements:
- Background in reference librarianship, archives, or special collections.
- Experience in investigative journalism or professional fact-checking.
- Experience with OSINT, due diligence, KYC, or investigative research.
- Background in patent, prior-art, or legal-discovery research.
- Experience with genealogy or historical records research.
- Experience with competitive quizzing, puzzle design, or puzzle-hunt construction.
- Familiarity with JSON or structured data formats.
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