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You will identify search-related failures in AI models by creating queries and documenting inadequate responses. Additionally, you will write instructions and evaluation criteria to ensure high-quality, region-specific search results.
Overview
Are you passionate about languages, writing, and quality evaluation? We are launching an exciting language evaluation project and are looking for Spanish-speaking experts to join our team.
What you will do:
Identify realistic search-related failures where an AI model provides inadequate responses. Create search queries, test them, document what went wrong, and write instructions and evaluation criteria for correct answers.
Common issues: local relevance, source quality, outdated information, language mismatches, incomplete answers, and region-specific inapplicability. Testing multiple queries before finding failures is expected.
Project Details:
- Start Date: ASAP
- Duration: Ongoing Project.
- Commitment: 20 hours per week.
- Job Type: Freelance contract.
- Location: Remote
- Rate: $30 per hour.
Requirements:
- Research skills — ability to find and verify information from multiple sources; comfort navigating different websites, databases, and documentation
- Critical thinking — Can spot contradictions between sources, identify outdated information, and recognize when something doesn't apply to a specific locale/context
- Attention to detail — Can catch nuances in language, local variations (prices, regulations, requirements), and edge cases
- Problem-solving mindset — Comfortable iterating and testing when things don't work; doesn't get frustrated by trial-and-error
- Domain knowledge — Ideally someone with background in research, quality assurance, compliance, or similar work that requires precision and source verification
- Writing clarity — Can articulate instructions and rubrics clearly so others understand the logic behind their reasoning
- Locale knowledge — Deep familiarity with their specific locale (local regulations, business practices, cultural nuances) is valuable for spotting region-specific failures
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