AI Evaluator for Digital Shopping Assistant
Job Description
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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.
You 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.
This 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 Do
- Review 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
Who Should Apply
- 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
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Terac
View Company ProfileTerac is an elite, enterprise-grade AI-native market research and expert data orchestration platform engineered to operate as the definitive, high-velocity infrastructure layer connecting frontier AI models and enterprise product teams with on-demand human expertise. Operating as a mission-critical "intelligence infrastructure layer" for the modern data economy, the company eliminates the severe operational friction of traditional qualitative research—which frequently suffers from slow participant sourcing, manual scheduling bottlenecks, and multi-week analysis cycles—by deploying automated, voice-based AI agents capable of conducting natural, personalized interviews with hundreds of participants simultaneously. Moving far beyond rigid legacy survey tools, Terac serves a dual purpose: it acts as a scalable consumer insights engine for product teams and a highly vetted marketplace for the human data economy, allowing frontier AI labs and research institutions to instantly tap into specialized, high-stakes human judgment for model evaluation and RLHF. Under the hood, their sophisticated proprietary validation infrastructure—backed by top-tier venture capital—natively handles automated participant recruitment, strict quality-control vetting, smart routing, multi-region payouts, and immediate programmatic synthesis of unstructured conversation into structured, actionable data graphs. What sets Terac apart is its uncompromising dedication to shifting how humans and AI collaborate at scale; by bridging the gap between performance-intensive, data-hungry enterprise workflows and accessible, flexible expert panels, the firm enables global technology organizations to radically accelerate their product-market loops, eliminate data engineering bottlenecks, and build an unassailable foundation for continuous model and product alignment.
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