
Mandarin Quality Control Lead
Posted Jul 27

Posted Jul 27
This is a fully remote position, open to applicants in Japan.
• Lead and oversee a team of around 10 Quality Control Reviewers, ensuring that consistent quality standards are upheld across the Mandarin Chinese locale.
• Evaluate reviewer feedback, conduct quality audits, and ensure compliance with project guidelines.
• Serve as the main quality point of contact for the Mandarin Chinese locale, addressing quality inquiries and escalating complex issues when needed.
• Facilitate calibration sessions and deliver structured coaching to enhance reviewer performance.
• Track quality trends, identify potential risks, and proactively tackle performance deficiencies.
• Assist in the onboarding and training of new Quality Control Reviewers.
• Collaborate with global Quality Teams to refine processes, documentation, and maintain quality consistency across AI training tasks.
• Native-level proficiency (CEFR C2 or equivalent) in Mandarin Chinese.
• Professional proficiency in written and spoken English.
• At least 2 years of experience in AI training, data annotation, linguistic quality, localization QA, or a comparable quality assurance position.
• A minimum of 1 year of experience leading or supervising reviewers, annotators, or quality teams.
• In-depth understanding of linguistic quality, including grammar, fluency, tone, register, and cultural subtleties.
• Proven experience in providing structured, evidence-based feedback and coaching others to enhance quality.
• Exceptional analytical skills with the capability to evaluate complex tasks where there may not be a single correct solution.
• Strong organizational abilities and the capacity to manage multiple priorities in a dynamic remote environment.
• Nice to have:
• A degree in Linguistics, Computer Science, Engineering, or another analytical discipline.
• Experience with Large Language Models (LLMs), RLHF, AI data annotation, prompt evaluation, or NLP projects.
• Familiarity with annotation platforms and quality management processes for AI datasets.
• Competitive salary and performance-based bonuses.
• Flexible work hours and remote working options.
• Opportunities for professional development and training.
• Collaborative and inclusive work environment.
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