Hindi-Speaking AI Localization Expert

The work

You will review AI-generated Hindi responses and create language content that is accurate, clear, culturally appropriate, and aligned with evaluation guidelines. You will also judge the quality of model reasoning and explain your decisions.

The role uses MQM and LQA concepts, which are structured ways to classify language and translation errors. Your reviews will help improve AI responses across different use cases.

  • Review Hindi AI responses for accuracy, clarity, and reasoning quality.
  • Write high-quality explanations, language content, and model solutions.
  • Evaluate and rank AI responses based on correctness and reasoning.
  • Find errors in methodology, conceptual understanding, or cultural nuance.
  • Fact-check units, references, names, dates, and other localized details.
  • Apply MQM and LQA error categories consistently.

What it pays and takes

This is a remote, part-time hourly contractor role. The listing includes an entry-level experience label, while the role requirements call for substantial professional localization experience.

  • Pay: $5-$20 USD per hour, with a listed hourly rate of $20.
  • Time requirement: 20 or more hours per week.
  • Location: India only.
  • Languages: Fluent Hindi and at least C1 English.
  • Experience: 5 or more years in professional localization or translation.
  • Education: Bachelor's degree or higher in Translation, Linguistics, Localization, or a related field.
  • Required skills: MQM and LQA error typology, CAT tools, QA workflows, and strong editorial judgment.
  • You should be able to assess register, tone, inclusivity, and cultural nuance.
  • Helpful background: AI training, annotation, evaluation, or multilingual localization experience.

How it works

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

About AI training work

AI training work is the human side of building artificial intelligence. Experts review examples, write responses, and judge model output so AI systems become more accurate, useful, and appropriate.

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