Ecosystem Content Research and Judgment Specialist (Mandarin Language) - Eco Governance, AI Data Service and Operations
May 13, 2026 Kuala Lumpur, Malaysia
About us
TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy.
- Size: 5,001 - 10,000 employees
- Industry: Entertainment & Gaming
Responsibilities
About the team
The AI Data Service and Operations (ADSO) team is responsible for providing safety and non-safety data annotation services and search operation services for all of the company's international products, which can also help international products build their own data ecological security.
Key Responsibilities
- Deeply participate in quality assurance for key data assets such as AI training data and test sets. Simultaneously handle content issue discovery and policy research/judgment, helping the team improve data credibility, judgment consistency, and overall delivery quality.
- Develop and maintain core standards, ensure effective policy implementation, and stay aligned with the latest policies, product updates, and industry best practices.
- Build quality evaluation systems; design, produce, and maintain high-quality test sets for calibration, quality assessment, and operational audits. Ensure comprehensive and balanced coverage across various scenarios, content types, complex cases, and edge cases.
- Identify misuse patterns and process vulnerabilities in operations, and provide support for key workflows such as arbitration, quality inspection, training, and calibration. Drive measurable improvements in review accuracy, consistency, and overall operational efficiency.
- Act as a key bridge for cross-departmental collaboration with policy, product, engineering, and other teams to ensure standards and solutions are practical and scalable. Track core metrics and participate in special projects to drive continuous improvement in execution quality and collaboration efficiency.
Qualifications
Minimum Qualification(s)
- Bachelor's degree or equivalent experience, along with strong interest in content ecosystems, platform governance, or AI data quality.
- Proficient in English as a primary working language and fluent in Mandarin Chinese for the purpose of reviewing, analyzing, and assessing content published in the Mandarin language.
- 1+ years of experience in quality assurance, content governance, content judgment/review, quality inspection, strategy, or related fields.
- Strong content comprehension ability, capable of handling non-standard content scenarios without clear-cut answers.
- Strong command of English with exceptional attention to detail, clarity, and linguistic consistency, and excellent written communication skills with emphasis on precision, clarity, and operational feasibility.
- Strong goal-oriented mindset and data-driven thinking. Proficient in using data analysis to identify and uncover problems, with clear logical reasoning.
Preferred Qualification(s)
- High level of self-motivation, solution-oriented thinking, and ability to multi-task, prioritize, and meet strict deadlines in a fast-paced, collaborative environment.
- Familiarity with machine-executable logic, labeling frameworks, or test-set workflows.
- Experience collaborating with Policy, Product, Governance, Engineering, or Training teams.
- Knowledge of scenario coverage, positive/negative balance, and dataset validation.
About the team
The AI Data Service and Operations (ADSO) team is responsible for providing safety and non-safety data annotation services and search operation services for all of the company's international products, which can also help international products build their own data ecological security.
Key Responsibilities
- Deeply participate in quality assurance for key data assets such as AI training data and test sets. Simultaneously handle content issue discovery and policy research/judgment, helping the team improve data credibility, judgment consistency, and overall delivery quality.
- Develop and maintain core standards, ensure effective policy implementation, and stay aligned with the latest policies, product updates, and industry best practices.
- Build quality evaluation systems; design, produce, and maintain high-quality test sets for calibration, quality assessment, and operational audits. Ensure comprehensive and balanced coverage across various scenarios, content types, complex cases, and edge cases.
- Identify misuse patterns and process vulnerabilities in operations, and provide support for key workflows such as arbitration, quality inspection, training, and calibration. Drive measurable improvements in review accuracy, consistency, and overall operational efficiency.
- Act as a key bridge for cross-departmental collaboration with policy, product, engineering, and other teams to ensure standards and solutions are practical and scalable. Track core metrics and participate in special projects to drive continuous improvement in execution quality and collaboration efficiency.
Minimum Qualification(s)
- Bachelor's degree or equivalent experience, along with strong interest in content ecosystems, platform governance, or AI data quality.
- Proficient in English as a primary working language and fluent in Mandarin Chinese for the purpose of reviewing, analyzing, and assessing content published in the Mandarin language.
- 1+ years of experience in quality assurance, content governance, content judgment/review, quality inspection, strategy, or related fields.
- Strong content comprehension ability, capable of handling non-standard content scenarios without clear-cut answers.
- Strong command of English with exceptional attention to detail, clarity, and linguistic consistency, and excellent written communication skills with emphasis on precision, clarity, and operational feasibility.
- Strong goal-oriented mindset and data-driven thinking. Proficient in using data analysis to identify and uncover problems, with clear logical reasoning.
Preferred Qualification(s)
- High level of self-motivation, solution-oriented thinking, and ability to multi-task, prioritize, and meet strict deadlines in a fast-paced, collaborative environment.
- Familiarity with machine-executable logic, labeling frameworks, or test-set workflows.
- Experience collaborating with Policy, Product, Governance, Engineering, or Training teams.
- Knowledge of scenario coverage, positive/negative balance, and dataset validation.
About the team
The AI Data Service and Operations (ADSO) team is responsible for providing safety and non-safety data annotation services and search operation services for all of the company's international products, which can also help international products build their own data ecological security.
Key Responsibilities
- Deeply participate in quality assurance for key data assets such as AI training data and test sets. Simultaneously handle content issue discovery and policy research/judgment, helping the team improve data credibility, judgment consistency, and overall delivery quality.
- Develop and maintain core standards, ensure effective policy implementation, and stay aligned with the latest policies, product updates, and industry best practices.
- Build quality evaluation systems; design, produce, and maintain high-quality test sets for calibration, quality assessment, and operational audits. Ensure comprehensive and balanced coverage across various scenarios, content types, complex cases, and edge cases.
- Identify misuse patterns and process vulnerabilities in operations, and provide support for key workflows such as arbitration, quality inspection, training, and calibration. Drive measurable improvements in review accuracy, consistency, and overall operational efficiency.
- Act as a key bridge for cross-departmental collaboration with policy, product, engineering, and other teams to ensure standards and solutions are practical and scalable. Track core metrics and participate in special projects to drive continuous improvement in execution quality and collaboration efficiency.
Qualifications
Minimum Qualification(s)
- Bachelor's degree or equivalent experience, along with strong interest in content ecosystems, platform governance, or AI data quality.
- Proficient in English as a primary working language and fluent in Mandarin Chinese for the purpose of reviewing, analyzing, and assessing content published in the Mandarin language.
- 1+ years of experience in quality assurance, content governance, content judgment/review, quality inspection, strategy, or related fields.
- Strong content comprehension ability, capable of handling non-standard content scenarios without clear-cut answers.
- Strong command of English with exceptional attention to detail, clarity, and linguistic consistency, and excellent written communication skills with emphasis on precision, clarity, and operational feasibility.
- Strong goal-oriented mindset and data-driven thinking. Proficient in using data analysis to identify and uncover problems, with clear logical reasoning.
Preferred Qualification(s)
- High level of self-motivation, solution-oriented thinking, and ability to multi-task, prioritize, and meet strict deadlines in a fast-paced, collaborative environment.
- Familiarity with machine-executable logic, labeling frameworks, or test-set workflows.
- Experience collaborating with Policy, Product, Governance, Engineering, or Training teams.
- Knowledge of scenario coverage, positive/negative balance, and dataset validation.
Responsibilities
ResponsibilitiesAbout the team
The AI Data Service and Operations (ADSO) team is responsible for providing safety and non-safety data annotation services and search operation services for all of the company's international products, which can also help international products build their own data ecological security.
Key Responsibilities
- Deeply participate in quality assurance for key data assets such as AI training data and test sets. Simultaneously handle content issue discovery and policy research/judgment, helping the team improve data credibility, judgment consistency, and overall delivery quality.
- Develop and maintain core standards, ensure effective policy implementation, and stay aligned with the latest policies, product updates, and industry best practices.
- Build quality evaluation systems; design, produce, and maintain high-quality test sets for calibration, quality assessment, and operational audits. Ensure comprehensive and balanced coverage across various scenarios, content types, complex cases, and edge cases.
- Identify misuse patterns and process vulnerabilities in operations, and provide support for key workflows such as arbitration, quality inspection, training, and calibration. Drive measurable improvements in review accuracy, consistency, and overall operational efficiency.
- Act as a key bridge for cross-departmental collaboration with policy, product, engineering, and other teams to ensure standards and solutions are practical and scalable. Track core metrics and participate in special projects to drive continuous improvement in execution quality and collaboration efficiency.
Qualifications
QualificationsMinimum Qualification(s)
- Bachelor's degree or equivalent experience, along with strong interest in content ecosystems, platform governance, or AI data quality.
- Proficient in English as a primary working language and fluent in Mandarin Chinese for the purpose of reviewing, analyzing, and assessing content published in the Mandarin language.
- 1+ years of experience in quality assurance, content governance, content judgment/review, quality inspection, strategy, or related fields.
- Strong content comprehension ability, capable of handling non-standard content scenarios without clear-cut answers.
- Strong command of English with exceptional attention to detail, clarity, and linguistic consistency, and excellent written communication skills with emphasis on precision, clarity, and operational feasibility.
- Strong goal-oriented mindset and data-driven thinking. Proficient in using data analysis to identify and uncover problems, with clear logical reasoning.
Preferred Qualification(s)
- High level of self-motivation, solution-oriented thinking, and ability to multi-task, prioritize, and meet strict deadlines in a fast-paced, collaborative environment.
- Familiarity with machine-executable logic, labeling frameworks, or test-set workflows.
- Experience collaborating with Policy, Product, Governance, Engineering, or Training teams.
- Knowledge of scenario coverage, positive/negative balance, and dataset validation.
Additional Information
- Job category: Operations
- Posted: May 13, 2026