Gujarati Expert with Mathematical Background

SME Careers

United States

Remote

USD 34,000 - 69,000

Part time

14 days+

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Job summary

SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, seeks a Gujarati Language Specialist (SME) for an hourly remote contractor role to review AI-generated Gujarati content and create high-quality Gujarati reference content.

You will assess outputs for accuracy, fluency, grammar, tone, cultural appropriateness, and provide precise written feedback in English, writing rewrites that demonstrate best practices in Gujarati writing.

Qualifications

  • Native or near-native Gujarati reading and writing required.
  • Strong professional English (C1) to follow guidelines and provide feedback in English.
  • 3+ years in writing, editing, localization, translation, content QA, journalism, education, or related language work.
  • Deep understanding of Gujarati grammar, spelling, punctuation, and style; able to explain fixes.

Responsibilities

  • Review AI-generated Gujarati content for accuracy, fluency, and tone.
  • Create high-quality Gujarati reference content across multiple domains.
  • Provide precise written feedback, rewrites, and model answers; rate AI outputs for quality and correctness.

Skills

Gujarati fluency
English proficiency (C1)
Content QA experience
Multilingual (Gujarati-English)

Education

Bachelor's degree in Mathematics

Job description

In this hourly, remote contractor role, you will work as a Gujarati Language Specialist (SME) to review AI-generated Gujarati content and/or create high-quality Gujarati reference content, evaluating language quality and step-by-step reasoning while providing precise written feedback. You will assess outputs for accuracy, fluency, grammar, spelling, tone, cultural appropriateness, and adherence to the prompt; identify errors in meaning, mistranslation, register (formal vs informal), ambiguity, and logical consistency; fact-check claims when needed; write high-quality rewrites and model answers that demonstrate best practices in Gujarati writing; and rate and compare multiple AI responses based on correctness and overall quality.

This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your Gujarati expertise directly helps improve the world’s premier AI models by making their Gujarati language output more natural, reliable, culturally accurate, and clearly written.

Responsibilities

  • Develop AI Training Content: Create prompts and gold-standard Gujarati answers across multiple domains (general knowledge, customer support, education, conversational writing).
  • Optimize AI Performance: Evaluate and rank AI outputs to improve fluency, correctness, tone match, and cultural appropriateness.
  • Ensure Model Integrity: Detect unsafe or misleading content, factual hallucinations, bias, and policy-risk language; validate reliability across use cases.

Requirements

  • Bachelor’s degree (or higher) in Mathematics
  • Native or near-native Gujarati proficiency (reading and writing required).
  • Strong professional proficiency in English (minimum C1) to follow guidelines and provide detailed feedback in English.
  • 3+ years of professional experience in writing, editing, localization, translation, content QA, journalism, education, or related language-focused work.
  • Deep understanding of Gujarati grammar, spelling conventions, punctuation, and style—able to explain why something is wrong and how to fix it.
  • Comfortable handling multiple registers (formal/informal), dialect variation, and audience adaptation (e.g., India vs diaspora audiences).
  • High attention to detail when spotting subtle meaning shifts, hallucinated claims, or culturally awkward phrasing.
  • Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones.
  • Prior experience with AI data training/annotation, translation QA, editorial QA, or rubric-based evaluation is strongly preferred.
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