We're hiring AI evaluators to assess the accuracy and helpfulness of a new digital shopping assistant. This project focuses on understanding how well the system handles real-world e-commerce queries and where it falls short in its logic. Your analysis will directly feed into improving the underlying model and its response quality.
How It WorksYou will review real interaction traces between users and the shopping assistant within our custom platform. As you analyze these conversations, you will pinpoint specific failures, logical errors, or unhelpful product recommendations. From there, you will create structured rubrics and verifiers to consistently judge future response quality. This is an ongoing remote engagement requiring 20+ hours per week.
Who This Is ForThis opportunity is ideal for quality assurance specialists, AI data evaluators, and e-commerce professionals with a strong eye for detail. We welcome applicants with prior experience in prompt engineering, complex data annotation, or software testing. You should be comfortable analyzing text interactions deeply and building structured evaluation frameworks from scratch.
What You'll DoReview real user interaction traces with an AI shopping assistant
Identify logical failures, inaccuracies, or poor recommendations in the text
Create structured rubrics and verifiers to judge response quality
Commit to 20+ hours per week of evaluation work on our internal platform
Experience in data evaluation, quality assurance, or AI training
Strong analytical skills with the ability to spot subtle errors in text
Familiarity with e-commerce search and digital shopping experiences
Ability to commit to a sustained workload of 20+ hours per week
$50 per hour
Start your paid interview now
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Learn more at terac.com or on YouTube at @jointerac.
Skills Required
- Experience in data evaluation, quality assurance, or AI training
- Strong analytical skills and ability to identify subtle errors in text
- Familiarity with e-commerce search and digital shopping experiences
- Ability to commit to a sustained workload of 20 or more hours per week
- Experience with prompt engineering, complex data annotation, or software testing
What We Do
Democratizing the future of company automation with AI
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