
Simplified Chinese QA Lead for AI Training Data
Overview
This remote contract role leads quality assurance for Mainland China Simplified Chinese AI training projects. You review AI-generated content and trainer outputs, ensuring alignment with project rubrics and cultural expectations. You document findings and maintain style guides and documentation to support onboarding and scalable QA. SME Careers, a subsidiary of SuperAnnotate, enables you to impact premier AI models by delivering natural, accurate, culturally appropriate Chinese training data.
What You'll Do8
- 1Spot-check Simplified Chinese items, flag issues, provide direct feedback via DMs, and escalate recurring quality problems.
- 2Update trainers and QAs on Discord with new guidelines, workflow updates, project changes, and quality expectations.
- 3Answer questions around Simplified Chinese wording, Mainland China terminology, punctuation, register, translation fidelity, and edge cases.
- 4DM inactive contributors, encourage activation, track follow-ups, and flag availability issues.
- 5Create and maintain Simplified Chinese documentation, style guides, trackers, FAQs, examples, honeypots, and onboarding materials.
- 6Run onboarding/training calls for Simplified Chinese contributors.
- 7Ensure Mainland China Simplified Chinese guidelines are applied consistently.
- 8Identify recurring quality gaps and build scalable QA processes.
Requirements10
- 1Bachelor's or Master's degree in Chinese, Mandarin, linguistics, translation, communications, journalism, English, education, quality assurance, or a related field.
- 2Native or near-native Simplified Chinese proficiency with strong Mainland China Mandarin writing judgment.
- 3Strong English proficiency to follow project guidelines, communicate with teams, and provide clear feedback in English.
- 43+ years of professional experience in Simplified Chinese writing, editing, translation, localization, content QA, AI training, annotation, or related language workflows.
- 5Strong understanding of Simplified Chinese grammar, punctuation, terminology, register, tone, Mainland China usage, cultural context, and localization expectations.
- 6Ability to evaluate Simplified Chinese content against detailed rubrics and identify issues such as mistranslation, traditional leakage, unnatural tone, Taiwan/Hong Kong terminology mismatch, hallucinated claims, ambiguity, or inconsistent terminology.
- 7Experience leading or supporting remote teams of trainers, annotators, reviewers, editors, or QAs is preferred.
- 8Comfort with Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems.
- 9Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, and documentation.
- 10Experience with AI training, data annotation, LLM evaluation, prompt/response evaluation, or rubric-based LLM QA is a strong plus.
Who Should Apply
Ideal candidates hold a degree in a related field and bring 3+ years in Simplified Chinese language workflows, with a track record of enforcing style guides and rubric-based evaluation. You excel at remote collaboration, guiding trainers and QAs through Discord and shared docs. This role is less suitable for applicants lacking native or near-native Simplified Chinese or without experience leading remote QA teams. Strong candidates demonstrate meticulous attention to detail, thorough documentation habits, and the ability to identify and address recurring quality gaps.
Salary Insight
Pay rate: $35/hr. This hourly rate aligns with other remote, contract QA leadership roles in AI training.
Location
Required Skills
Application Tip
Include a concrete example of a rubric you designed for Simplified Chinese QA and a brief note on how you improved data quality through documentation.
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How your application is processed
1Application received
Your resume and details are logged the moment you apply.
2ATS + eligibility screening
We check your profile against the role’s skills, seniority, and requirements.
3Employer sees qualified profiles only
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