AI Data Strategy Program Manager - AI Data Service Operations (Safety Model Operations)
Mar 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: 10,000+ employees
- Industry: Technology: Consumer Internet
Why you should apply for a job to TikTok:
4.5/5 in overall job satisfaction
4.5/5 in supportive management
100% say women are treated fairly and equally to men
100% would recommend this company to other women
100% say the CEO supports gender diversity
Ratings are based on anonymous reviews by Fairygodboss members. See all reviews ›
Responsibilities
Our Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.
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.
The Safety Model Operations [SMO] team within ADSO is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.
What will I do?
1. Responsible for end-to-end project delivery management for content safety model training and evaluation data - from requirements analysis and solution design to execution and continuous optimization - ensuring projects are completed efficiently and with high quality.
2. Deeply understand business goals and data requirements from algorithm, product, and other teams. Lead the development and iteration of data production strategies, transforming complex business problems into actionable, scalable data solutions.
3. Establish and continuously optimize standardized processes, operational guidelines, and quality systems for data production. Identify efficiency bottlenecks and quality risks, and improve delivery efficiency and stability through mechanism design, tooling, and automation.
4. Act as the core driver of projects, coordinating with algorithm, product, annotation, operations, and other cross-functional teams. Manage project timelines, identify and resolve blockers and risks to ensure objectives are met.
5. Build quality assessment and retrospective mechanisms for project delivery. Use data monitoring, root cause analysis, and case studies to drive continuous improvement in delivery quality and team effectiveness, while establishing reusable best practices.
Qualifications
Minimum Qualifications
1. Bachelor's degree or higher in Computer Science, Data Science, Statistics, Information Management, Artificial Intelligence, or related fields along with 5 years of relevant working experience.
2. Excellent logical thinking and problem decomposition skills. Ability to quickly grasp business needs and design practical, executable data production strategies and plans.
3. Strong experience in full-cycle project management and process design/standardization. Skilled at identifying optimization opportunities and driving improvements; possesses systems-thinking and solution architecture mindset.
4. In-depth knowledge of machine learning and large model data production pipelines, including key stages and quality control points in "data collection/annotation - model training - model evaluation".
5. Solid data analysis skills to identify process issues and opportunities via insights; proficient with SQL and Excel for analysis and retrospectives.
6. Outstanding cross-functional communication and project leadership skills. Able to align resources and drive execution; clear logic and rigorous documentation skills for high-quality project docs and reports.
7. Highly self-driven with strong ownership mindset; capable of proactively solving problems and delivering results in a fast-paced, multi-task environment.
Preferred Qualifications
- Experience in model data production, data labeling/annotation project management, or data solution design.
- Hands-on experience with data analysis tools/languages (Python, R).
- Background in process automation, tool development, or building quality management systems.
- Experience with AI Agents, LLMs, or Prompt Engineering is a strong plus.
Our Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.
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.
The Safety Model Operations [SMO] team within ADSO is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.
What will I do?
1. Responsible for end-to-end project delivery management for content safety model training and evaluation data - from requirements analysis and solution design to execution and continuous optimization - ensuring projects are completed efficiently and with high quality.
2. Deeply understand business goals and data requirements from algorithm, product, and other teams. Lead the development and iteration of data production strategies, transforming complex business problems into actionable, scalable data solutions.
3. Establish and continuously optimize standardized processes, operational guidelines, and quality systems for data production. Identify efficiency bottlenecks and quality risks, and improve delivery efficiency and stability through mechanism design, tooling, and automation.
4. Act as the core driver of projects, coordinating with algorithm, product, annotation, operations, and other cross-functional teams. Manage project timelines, identify and resolve blockers and risks to ensure objectives are met.
5. Build quality assessment and retrospective mechanisms for project delivery. Use data monitoring, root cause analysis, and case studies to drive continuous improvement in delivery quality and team effectiveness, while establishing reusable best practices.
Minimum Qualifications
1. Bachelor's degree or higher in Computer Science, Data Science, Statistics, Information Management, Artificial Intelligence, or related fields along with 5 years of relevant working experience.
2. Excellent logical thinking and problem decomposition skills. Ability to quickly grasp business needs and design practical, executable data production strategies and plans.
3. Strong experience in full-cycle project management and process design/standardization. Skilled at identifying optimization opportunities and driving improvements; possesses systems-thinking and solution architecture mindset.
4. In-depth knowledge of machine learning and large model data production pipelines, including key stages and quality control points in "data collection/annotation - model training - model evaluation".
5. Solid data analysis skills to identify process issues and opportunities via insights; proficient with SQL and Excel for analysis and retrospectives.
6. Outstanding cross-functional communication and project leadership skills. Able to align resources and drive execution; clear logic and rigorous documentation skills for high-quality project docs and reports.
7. Highly self-driven with strong ownership mindset; capable of proactively solving problems and delivering results in a fast-paced, multi-task environment.
Preferred Qualifications
- Experience in model data production, data labeling/annotation project management, or data solution design.
- Hands-on experience with data analysis tools/languages (Python, R).
- Background in process automation, tool development, or building quality management systems.
- Experience with AI Agents, LLMs, or Prompt Engineering is a strong plus.
Our Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.
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.
The Safety Model Operations [SMO] team within ADSO is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.
What will I do?
1. Responsible for end-to-end project delivery management for content safety model training and evaluation data - from requirements analysis and solution design to execution and continuous optimization - ensuring projects are completed efficiently and with high quality.
2. Deeply understand business goals and data requirements from algorithm, product, and other teams. Lead the development and iteration of data production strategies, transforming complex business problems into actionable, scalable data solutions.
3. Establish and continuously optimize standardized processes, operational guidelines, and quality systems for data production. Identify efficiency bottlenecks and quality risks, and improve delivery efficiency and stability through mechanism design, tooling, and automation.
4. Act as the core driver of projects, coordinating with algorithm, product, annotation, operations, and other cross-functional teams. Manage project timelines, identify and resolve blockers and risks to ensure objectives are met.
5. Build quality assessment and retrospective mechanisms for project delivery. Use data monitoring, root cause analysis, and case studies to drive continuous improvement in delivery quality and team effectiveness, while establishing reusable best practices.
Qualifications
Minimum Qualifications
1. Bachelor's degree or higher in Computer Science, Data Science, Statistics, Information Management, Artificial Intelligence, or related fields along with 5 years of relevant working experience.
2. Excellent logical thinking and problem decomposition skills. Ability to quickly grasp business needs and design practical, executable data production strategies and plans.
3. Strong experience in full-cycle project management and process design/standardization. Skilled at identifying optimization opportunities and driving improvements; possesses systems-thinking and solution architecture mindset.
4. In-depth knowledge of machine learning and large model data production pipelines, including key stages and quality control points in "data collection/annotation - model training - model evaluation".
5. Solid data analysis skills to identify process issues and opportunities via insights; proficient with SQL and Excel for analysis and retrospectives.
6. Outstanding cross-functional communication and project leadership skills. Able to align resources and drive execution; clear logic and rigorous documentation skills for high-quality project docs and reports.
7. Highly self-driven with strong ownership mindset; capable of proactively solving problems and delivering results in a fast-paced, multi-task environment.
Preferred Qualifications
- Experience in model data production, data labeling/annotation project management, or data solution design.
- Hands-on experience with data analysis tools/languages (Python, R).
- Background in process automation, tool development, or building quality management systems.
- Experience with AI Agents, LLMs, or Prompt Engineering is a strong plus.
Responsibilities
ResponsibilitiesOur Company will be prioritizing applicants who have a current right to work in Singapore, and do not require Our Company's sponsorship of a visa.
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.
The Safety Model Operations [SMO] team within ADSO is responsible for building, optimizing, and maintaining machine learning models and operational processes that support TikTok's Trust & Safety systems. We ensure that automated safety models perform effectively in identifying harmful content, mitigating risks, and maintaining a safe user environment across regions.
What will I do?
1. Responsible for end-to-end project delivery management for content safety model training and evaluation data - from requirements analysis and solution design to execution and continuous optimization - ensuring projects are completed efficiently and with high quality.
2. Deeply understand business goals and data requirements from algorithm, product, and other teams. Lead the development and iteration of data production strategies, transforming complex business problems into actionable, scalable data solutions.
3. Establish and continuously optimize standardized processes, operational guidelines, and quality systems for data production. Identify efficiency bottlenecks and quality risks, and improve delivery efficiency and stability through mechanism design, tooling, and automation.
4. Act as the core driver of projects, coordinating with algorithm, product, annotation, operations, and other cross-functional teams. Manage project timelines, identify and resolve blockers and risks to ensure objectives are met.
5. Build quality assessment and retrospective mechanisms for project delivery. Use data monitoring, root cause analysis, and case studies to drive continuous improvement in delivery quality and team effectiveness, while establishing reusable best practices.
Qualifications
QualificationsMinimum Qualifications
1. Bachelor's degree or higher in Computer Science, Data Science, Statistics, Information Management, Artificial Intelligence, or related fields along with 5 years of relevant working experience.
2. Excellent logical thinking and problem decomposition skills. Ability to quickly grasp business needs and design practical, executable data production strategies and plans.
3. Strong experience in full-cycle project management and process design/standardization. Skilled at identifying optimization opportunities and driving improvements; possesses systems-thinking and solution architecture mindset.
4. In-depth knowledge of machine learning and large model data production pipelines, including key stages and quality control points in "data collection/annotation - model training - model evaluation".
5. Solid data analysis skills to identify process issues and opportunities via insights; proficient with SQL and Excel for analysis and retrospectives.
6. Outstanding cross-functional communication and project leadership skills. Able to align resources and drive execution; clear logic and rigorous documentation skills for high-quality project docs and reports.
7. Highly self-driven with strong ownership mindset; capable of proactively solving problems and delivering results in a fast-paced, multi-task environment.
Preferred Qualifications
- Experience in model data production, data labeling/annotation project management, or data solution design.
- Hands-on experience with data analysis tools/languages (Python, R).
- Background in process automation, tool development, or building quality management systems.
- Experience with AI Agents, LLMs, or Prompt Engineering is a strong plus.
Additional Information
- Job category: Operations
- Posted: Mar 6, 2026