[ADSO] Eco & Social Creation Policy Quality and Enforcement Lead - Singapore
Aug 6, 2026 Singapore
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 provides safety and non-safety data annotation services, search operation services, and customer services for TikTok's international products, helping them to build their own data ecological security. In order to optimize user experience while upholding negative content governance on our platforms, the Eco & Social Creation within ADSO focuses on data labeling work to support online content strategies and AI/LLM model development.
As the ADSO Quality Policy Quality and Enforcement Lead, you will champion the integrity and precision of TikTok's machine learning and LLM models on a global scale. Operating at the intersection of AI development, human-in-the-loop data labeling, and quality monitoring, you will lead global strategies to evaluate, refine, and deliver high-quality training data. You are responsible for ensuring that AI-driven content labeling aligns perfectly with platform policies, regional regulations, and global community guidelines.
Responsibilities
- Strategy & Delivery Management: Direct the end-to-end delivery of Ecosystem Key Metrics data operations and quality assurance initiatives across regional and multiple markets.
- Policy Understanding: Develop a strong understanding and methodology of policies and translate that understanding into accurate, consistent quality standards for data labeling and enforcement.
- Quality Frameworks: Establish, maintain, and continuously optimize data labeling guidelines, calibration protocols, and quality assessment procedures for diverse global markets.
- Risk & Incident Management: Leading Quality Assurance teams to conduct periodic Root Cause Analysis (RCA) on guideline ambiguities, performance gaps, or high-severity escalations, executing swift corrective actions.
- Operational Management: Allocate and optimize resources, manage workforce planning and task prioritization, and ensure output volume, delivery timelines, and operational targets consistently meet expectations.
- Performance Management: Conduct periodic performance evaluations for Quality Assurance teams and provide effective coaching to enhance performance outcomes.
- Vendor & Stakeholder Oversight: Manage relationships and performance metrics with global BPO partners and vendor sites. Ensure deliverables meet strict productivity and quality targets.
- AI Model Enhancement: Collaborate with XFNs, translate data insights into actionable improvements for Large Language Models (LLMs) and Ecosystems.
- Initiatives: Collaborate with stakeholders on ad-hoc tasks and initiate if required.
Qualifications
Minimum Qualification(s):
- Experience: Minimum 5 years of experience in Data operations, Trust & Safety, content moderation field, or AI data delivery-with a proven track record of managing global or cross-regional functions.
- Technical Acumen: Strong understanding of machine learning pipelines, LLMs, and hybrid (human-machine) data labeling frameworks.
- Leadership & Influence: Exceptional global stakeholder management. Ability to drive operational excellence in highly ambiguous, fast-paced, and cross-cultural environments. Understanding BCP Management during unexpected situations.
- Data-Driven: Proficiency in data analysis, dashboard creation (e.g., SQL, Excel), and using performance data to drive continuous improvements.
- Task-Driven: Strong logical thinking to evaluate the requests and prioritize the tasks.
- Tooling-Driven: Proficiency in using human moderation tools, content management systems and people management systems.
- Global Perspective: Strong awareness of global socio-cultural landscapes, online safety & user experience regulatory frameworks, and diverse market sensitivities; proficiency in English is required.
About the team
The AI Data Service and Operations (ADSO) team provides safety and non-safety data annotation services, search operation services, and customer services for TikTok's international products, helping them to build their own data ecological security. In order to optimize user experience while upholding negative content governance on our platforms, the Eco & Social Creation within ADSO focuses on data labeling work to support online content strategies and AI/LLM model development.
As the ADSO Quality Policy Quality and Enforcement Lead, you will champion the integrity and precision of TikTok's machine learning and LLM models on a global scale. Operating at the intersection of AI development, human-in-the-loop data labeling, and quality monitoring, you will lead global strategies to evaluate, refine, and deliver high-quality training data. You are responsible for ensuring that AI-driven content labeling aligns perfectly with platform policies, regional regulations, and global community guidelines.
Responsibilities
- Strategy & Delivery Management: Direct the end-to-end delivery of Ecosystem Key Metrics data operations and quality assurance initiatives across regional and multiple markets.
- Policy Understanding: Develop a strong understanding and methodology of policies and translate that understanding into accurate, consistent quality standards for data labeling and enforcement.
- Quality Frameworks: Establish, maintain, and continuously optimize data labeling guidelines, calibration protocols, and quality assessment procedures for diverse global markets.
- Risk & Incident Management: Leading Quality Assurance teams to conduct periodic Root Cause Analysis (RCA) on guideline ambiguities, performance gaps, or high-severity escalations, executing swift corrective actions.
- Operational Management: Allocate and optimize resources, manage workforce planning and task prioritization, and ensure output volume, delivery timelines, and operational targets consistently meet expectations.
- Performance Management: Conduct periodic performance evaluations for Quality Assurance teams and provide effective coaching to enhance performance outcomes.
- Vendor & Stakeholder Oversight: Manage relationships and performance metrics with global BPO partners and vendor sites. Ensure deliverables meet strict productivity and quality targets.
- AI Model Enhancement: Collaborate with XFNs, translate data insights into actionable improvements for Large Language Models (LLMs) and Ecosystems.
- Initiatives: Collaborate with stakeholders on ad-hoc tasks and initiate if required.
Minimum Qualification(s):
- Experience: Minimum 5 years of experience in Data operations, Trust & Safety, content moderation field, or AI data delivery-with a proven track record of managing global or cross-regional functions.
- Technical Acumen: Strong understanding of machine learning pipelines, LLMs, and hybrid (human-machine) data labeling frameworks.
- Leadership & Influence: Exceptional global stakeholder management. Ability to drive operational excellence in highly ambiguous, fast-paced, and cross-cultural environments. Understanding BCP Management during unexpected situations.
- Data-Driven: Proficiency in data analysis, dashboard creation (e.g., SQL, Excel), and using performance data to drive continuous improvements.
- Task-Driven: Strong logical thinking to evaluate the requests and prioritize the tasks.
- Tooling-Driven: Proficiency in using human moderation tools, content management systems and people management systems.
- Global Perspective: Strong awareness of global socio-cultural landscapes, online safety & user experience regulatory frameworks, and diverse market sensitivities; proficiency in English is required.
About the team
The AI Data Service and Operations (ADSO) team provides safety and non-safety data annotation services, search operation services, and customer services for TikTok's international products, helping them to build their own data ecological security. In order to optimize user experience while upholding negative content governance on our platforms, the Eco & Social Creation within ADSO focuses on data labeling work to support online content strategies and AI/LLM model development.
As the ADSO Quality Policy Quality and Enforcement Lead, you will champion the integrity and precision of TikTok's machine learning and LLM models on a global scale. Operating at the intersection of AI development, human-in-the-loop data labeling, and quality monitoring, you will lead global strategies to evaluate, refine, and deliver high-quality training data. You are responsible for ensuring that AI-driven content labeling aligns perfectly with platform policies, regional regulations, and global community guidelines.
Responsibilities
- Strategy & Delivery Management: Direct the end-to-end delivery of Ecosystem Key Metrics data operations and quality assurance initiatives across regional and multiple markets.
- Policy Understanding: Develop a strong understanding and methodology of policies and translate that understanding into accurate, consistent quality standards for data labeling and enforcement.
- Quality Frameworks: Establish, maintain, and continuously optimize data labeling guidelines, calibration protocols, and quality assessment procedures for diverse global markets.
- Risk & Incident Management: Leading Quality Assurance teams to conduct periodic Root Cause Analysis (RCA) on guideline ambiguities, performance gaps, or high-severity escalations, executing swift corrective actions.
- Operational Management: Allocate and optimize resources, manage workforce planning and task prioritization, and ensure output volume, delivery timelines, and operational targets consistently meet expectations.
- Performance Management: Conduct periodic performance evaluations for Quality Assurance teams and provide effective coaching to enhance performance outcomes.
- Vendor & Stakeholder Oversight: Manage relationships and performance metrics with global BPO partners and vendor sites. Ensure deliverables meet strict productivity and quality targets.
- AI Model Enhancement: Collaborate with XFNs, translate data insights into actionable improvements for Large Language Models (LLMs) and Ecosystems.
- Initiatives: Collaborate with stakeholders on ad-hoc tasks and initiate if required.
Qualifications
Minimum Qualification(s):
- Experience: Minimum 5 years of experience in Data operations, Trust & Safety, content moderation field, or AI data delivery-with a proven track record of managing global or cross-regional functions.
- Technical Acumen: Strong understanding of machine learning pipelines, LLMs, and hybrid (human-machine) data labeling frameworks.
- Leadership & Influence: Exceptional global stakeholder management. Ability to drive operational excellence in highly ambiguous, fast-paced, and cross-cultural environments. Understanding BCP Management during unexpected situations.
- Data-Driven: Proficiency in data analysis, dashboard creation (e.g., SQL, Excel), and using performance data to drive continuous improvements.
- Task-Driven: Strong logical thinking to evaluate the requests and prioritize the tasks.
- Tooling-Driven: Proficiency in using human moderation tools, content management systems and people management systems.
- Global Perspective: Strong awareness of global socio-cultural landscapes, online safety & user experience regulatory frameworks, and diverse market sensitivities; proficiency in English is required.
Responsibilities
ResponsibilitiesAbout the team
The AI Data Service and Operations (ADSO) team provides safety and non-safety data annotation services, search operation services, and customer services for TikTok's international products, helping them to build their own data ecological security. In order to optimize user experience while upholding negative content governance on our platforms, the Eco & Social Creation within ADSO focuses on data labeling work to support online content strategies and AI/LLM model development.
As the ADSO Quality Policy Quality and Enforcement Lead, you will champion the integrity and precision of TikTok's machine learning and LLM models on a global scale. Operating at the intersection of AI development, human-in-the-loop data labeling, and quality monitoring, you will lead global strategies to evaluate, refine, and deliver high-quality training data. You are responsible for ensuring that AI-driven content labeling aligns perfectly with platform policies, regional regulations, and global community guidelines.
Responsibilities
- Strategy & Delivery Management: Direct the end-to-end delivery of Ecosystem Key Metrics data operations and quality assurance initiatives across regional and multiple markets.
- Policy Understanding: Develop a strong understanding and methodology of policies and translate that understanding into accurate, consistent quality standards for data labeling and enforcement.
- Quality Frameworks: Establish, maintain, and continuously optimize data labeling guidelines, calibration protocols, and quality assessment procedures for diverse global markets.
- Risk & Incident Management: Leading Quality Assurance teams to conduct periodic Root Cause Analysis (RCA) on guideline ambiguities, performance gaps, or high-severity escalations, executing swift corrective actions.
- Operational Management: Allocate and optimize resources, manage workforce planning and task prioritization, and ensure output volume, delivery timelines, and operational targets consistently meet expectations.
- Performance Management: Conduct periodic performance evaluations for Quality Assurance teams and provide effective coaching to enhance performance outcomes.
- Vendor & Stakeholder Oversight: Manage relationships and performance metrics with global BPO partners and vendor sites. Ensure deliverables meet strict productivity and quality targets.
- AI Model Enhancement: Collaborate with XFNs, translate data insights into actionable improvements for Large Language Models (LLMs) and Ecosystems.
- Initiatives: Collaborate with stakeholders on ad-hoc tasks and initiate if required.
Qualifications
QualificationsMinimum Qualification(s):
- Experience: Minimum 5 years of experience in Data operations, Trust & Safety, content moderation field, or AI data delivery-with a proven track record of managing global or cross-regional functions.
- Technical Acumen: Strong understanding of machine learning pipelines, LLMs, and hybrid (human-machine) data labeling frameworks.
- Leadership & Influence: Exceptional global stakeholder management. Ability to drive operational excellence in highly ambiguous, fast-paced, and cross-cultural environments. Understanding BCP Management during unexpected situations.
- Data-Driven: Proficiency in data analysis, dashboard creation (e.g., SQL, Excel), and using performance data to drive continuous improvements.
- Task-Driven: Strong logical thinking to evaluate the requests and prioritize the tasks.
- Tooling-Driven: Proficiency in using human moderation tools, content management systems and people management systems.
- Global Perspective: Strong awareness of global socio-cultural landscapes, online safety & user experience regulatory frameworks, and diverse market sensitivities; proficiency in English is required.
Additional Information
- Job category: Operations
- Posted: Aug 6, 2026