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6 дней назад

Labeler / Annotator – AI Response Evaluation (Chinese: Simplified & Traditional)

40 800 - 46 400MXN
Формат работы
remote (только Mexico/Brazil/Argentina)
Тип работы
fulltime
Английский
b2
Страна
US/Argentina/Mexico +1 еще
Вакансия из списка Hirify.GlobalВакансия из Hirify Global, списка международных tech-компаний
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Описание вакансии

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TL;DR

Labeler / Annotator (AI Response Evaluation, Chinese): Perform side-by-side comparisons of AI-generated responses across Q&A, web search, file/image tasks, and conversations with an accent on accuracy, relevance, clarity, instruction-following, and cultural nuances in Simplified and Traditional Chinese. Focus on applying detailed annotation guidelines and maintaining consistent high-quality evaluations.

Location: Remote

Salary: MXN $40,800 – $46,400 (monthly equivalent, full-time)

Company

Technology solutions firm headquartered in Bellevue, Washington, with presence across the US and expanding in LATAM.

What you will do

  • Evaluate AI responses in side-by-side (SBS) comparisons across general Q&A, web search, file/image tasks, and single/multi-turn conversations
  • Assess outputs for accuracy, relevance, clarity, and instruction-following
  • Identify nuances in tone, meaning, and cultural context between Chinese variants
  • Apply scenario-specific annotation guidelines consistently

Requirements

  • Native or professional fluency in Chinese (both Simplified and Traditional)
  • Strong English reading comprehension (for guidelines)
  • Prior experience with side-by-side (SBS) labeling or annotation
  • Excellent analytical thinking and attention to detail
  • Ability to quickly understand and apply structured evaluation frameworks

Nice to have

  • Background in linguistics, translation, or localization
  • Experience in AI evaluation, data annotation, or search relevance analysis

Culture & Benefits

  • Hired through EOR partner with locally compliant benefits including paid vacation, aguinaldo, vacation premium, social security, and healthcare (IMSS)
  • Structured onboarding with training, practice, and qualification review
  • Work on cutting-edge AI systems as part of a global, multilingual team
  • Build transferable AI evaluation skills contributing to real-world AI improvements

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