Web Research Specialist (English, Benchmark Design)

You will create research problems that remain difficult for AI browsing agents, even when they have full web access. Each problem should lead to a short, stable answer that can be checked against reliable sources.

This listing uses the title Web Research Specialist, while the duties focus on benchmark design. Review the duties and qualifications before applying.

• Write natural-language research questions with objectively verifiable answers.
• Create independent clues involving dates, people, places, organizations, works, events, records, and quantities.
• Research primary sources such as government and institutional databases, archives, registries, and PDF documents.
• Record the searches you performed and the results they returned.
• Cite exact pages, tables, and sections to create a complete evidence trail.
• Deliver structured research outputs; familiarity with JSON is helpful.

This is an intermediate, part-time contract role. The work requires careful investigation, precise sourcing, and extensive structured documentation.

• Pay: $30 per label.
• Time: 20 or more hours per week.
• Location: Open worldwide.
• Language: Fluent written English.
• Education or experience: A master's degree or more than three years of relevant experience.
• Research: Demonstrated open-web research ability and confidence investigating unfamiliar subjects from the beginning.
• Documentation: Strong sourcing precision, including citations to exact pages, tables, and sections.
• Relevant experience: LLM evaluation, red-teaming, or benchmark construction.
• Helpful backgrounds: Reference librarianship, archival research, special collections, investigative journalism, professional fact-checking, OSINT, due diligence, KYC, patent or prior-art searching, legal discovery, genealogy, competitive quizzing, or puzzle-hunt construction.
• Technical: Familiarity with JSON and structured data delivery formats is useful.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training work is the human side of building artificial intelligence. People create examples, review model responses, evaluate results, and prepare reliable data so AI systems can improve; experienced contributors are valued for careful judgment and subject knowledge.