Model Data Operations Specialist, Evaluation & Judgement Center, Platform Responsibility
Mar 23, 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 Platform Responsibility team is bringing disruptive innovation to content safety through the deep application of AI. We are building next-generation infrastructure that leverages advanced LLMs to reshape risk detection and governance. By engineering high-quality data pipelines and integrating AI into core decision-making, we drive exponential efficiency gains and precision. Working at the intersection of scalable engineering and technology, we empower global business growth while serving as the foundation of user trust.
About the Role
Under the spirit of TikTok Community Guidelines, the team leverages the capabilities of LLM and prompt engineering to deliver a large model Agent that can represent "absolute correctness", providing stable evaluation capabilities for TikTok content safety. This role will lead the team to refine strategy operations and prompt optimization to enhance the Agent's precise recall ability for risky content.
Responsibilities:
- Undertake AI special projects for product R&D, perform tasks such as annotation of the LLM model training data sample set, evaluation of model iteration effectiveness, industry application research, and security compliance assurance. Cooperate closely with upstream product technology to jointly promote the achievement of business objectives.
- Standardise Definitions: Responsible for the definition and access criteria of the Golden Set across all risk domains (pornography, violence and terrorism, politics-related, abuse, etc.). Convert qualitative Policy documents into quantitative annotation SOPs executable by the Data Ops team.
- Ground Truth Delivery: Responsible for key aspects of queue delivery, including but not limited to demand analysis, acceptance, solution customization and training, quality assurance, delivery, etc.
- Operation of the Adjudication Mechanism: Establish an adjudication mechanism for internal cases to align consistent judgments on risk issues of different levels.
- Based on an understanding of LLM content safety process design and Community Guidelines, design rule routing logic suitable for LLM execution, and continuously optimize and iterate to improve model performance and resource utilization efficiency.
- Establish an AI content quality management system, be responsible for quality results, and continuously conduct work such as problem diagnosis, data analysis, and model optimization.
Qualifications
Minimum Qualifications:
- Bachelor's degree or above, with 3+ years of experience in model operations, AI/ML operations, or related domains.
- Demonstrated ability to lead community policy development and collaborate effectively across Product, Engineering, and Operations teams. Strong problem-solving skills with the ability to identify root causes, prioritize initiatives, develop structured improvement roadmaps, drive execution, and measure impact through clear success metrics.
- Deep interest in internet products and strong awareness of AI industry trends. Familiarity with mainstream LLM products (e.g., ChatGPT, Gemini, etc.) and hands-on experience in model training, evaluation, or prompt engineering.
- Highly data-sensitive with strong analytical capabilities. Able to translate data insights into actionable strategies, synthesize complex findings, and proactively drive resolution of operational or model-related issues.
- Demonstrated understanding of community safety frameworks and risk governance. Strong risk awareness and accountability, with the ability to proactively identify content, model, or process risks and design scalable mitigation solutions.
Preferred Qualifications
- Background in product management or technical experience in search systems, artificial intelligence, or large language models are strongly preferred.
- Self-motivated and results-driven, able to influence stakeholders in fast-paced, ambiguous environments.
About the Team
The Platform Responsibility team is bringing disruptive innovation to content safety through the deep application of AI. We are building next-generation infrastructure that leverages advanced LLMs to reshape risk detection and governance. By engineering high-quality data pipelines and integrating AI into core decision-making, we drive exponential efficiency gains and precision. Working at the intersection of scalable engineering and technology, we empower global business growth while serving as the foundation of user trust.
About the Role
Under the spirit of TikTok Community Guidelines, the team leverages the capabilities of LLM and prompt engineering to deliver a large model Agent that can represent "absolute correctness", providing stable evaluation capabilities for TikTok content safety. This role will lead the team to refine strategy operations and prompt optimization to enhance the Agent's precise recall ability for risky content.
Responsibilities:
- Undertake AI special projects for product R&D, perform tasks such as annotation of the LLM model training data sample set, evaluation of model iteration effectiveness, industry application research, and security compliance assurance. Cooperate closely with upstream product technology to jointly promote the achievement of business objectives.
- Standardise Definitions: Responsible for the definition and access criteria of the Golden Set across all risk domains (pornography, violence and terrorism, politics-related, abuse, etc.). Convert qualitative Policy documents into quantitative annotation SOPs executable by the Data Ops team.
- Ground Truth Delivery: Responsible for key aspects of queue delivery, including but not limited to demand analysis, acceptance, solution customization and training, quality assurance, delivery, etc.
- Operation of the Adjudication Mechanism: Establish an adjudication mechanism for internal cases to align consistent judgments on risk issues of different levels.
- Based on an understanding of LLM content safety process design and Community Guidelines, design rule routing logic suitable for LLM execution, and continuously optimize and iterate to improve model performance and resource utilization efficiency.
- Establish an AI content quality management system, be responsible for quality results, and continuously conduct work such as problem diagnosis, data analysis, and model optimization.
Minimum Qualifications:
- Bachelor's degree or above, with 3+ years of experience in model operations, AI/ML operations, or related domains.
- Demonstrated ability to lead community policy development and collaborate effectively across Product, Engineering, and Operations teams. Strong problem-solving skills with the ability to identify root causes, prioritize initiatives, develop structured improvement roadmaps, drive execution, and measure impact through clear success metrics.
- Deep interest in internet products and strong awareness of AI industry trends. Familiarity with mainstream LLM products (e.g., ChatGPT, Gemini, etc.) and hands-on experience in model training, evaluation, or prompt engineering.
- Highly data-sensitive with strong analytical capabilities. Able to translate data insights into actionable strategies, synthesize complex findings, and proactively drive resolution of operational or model-related issues.
- Demonstrated understanding of community safety frameworks and risk governance. Strong risk awareness and accountability, with the ability to proactively identify content, model, or process risks and design scalable mitigation solutions.
Preferred Qualifications
- Background in product management or technical experience in search systems, artificial intelligence, or large language models are strongly preferred.
- Self-motivated and results-driven, able to influence stakeholders in fast-paced, ambiguous environments.
About the Team
The Platform Responsibility team is bringing disruptive innovation to content safety through the deep application of AI. We are building next-generation infrastructure that leverages advanced LLMs to reshape risk detection and governance. By engineering high-quality data pipelines and integrating AI into core decision-making, we drive exponential efficiency gains and precision. Working at the intersection of scalable engineering and technology, we empower global business growth while serving as the foundation of user trust.
About the Role
Under the spirit of TikTok Community Guidelines, the team leverages the capabilities of LLM and prompt engineering to deliver a large model Agent that can represent "absolute correctness", providing stable evaluation capabilities for TikTok content safety. This role will lead the team to refine strategy operations and prompt optimization to enhance the Agent's precise recall ability for risky content.
Responsibilities:
- Undertake AI special projects for product R&D, perform tasks such as annotation of the LLM model training data sample set, evaluation of model iteration effectiveness, industry application research, and security compliance assurance. Cooperate closely with upstream product technology to jointly promote the achievement of business objectives.
- Standardise Definitions: Responsible for the definition and access criteria of the Golden Set across all risk domains (pornography, violence and terrorism, politics-related, abuse, etc.). Convert qualitative Policy documents into quantitative annotation SOPs executable by the Data Ops team.
- Ground Truth Delivery: Responsible for key aspects of queue delivery, including but not limited to demand analysis, acceptance, solution customization and training, quality assurance, delivery, etc.
- Operation of the Adjudication Mechanism: Establish an adjudication mechanism for internal cases to align consistent judgments on risk issues of different levels.
- Based on an understanding of LLM content safety process design and Community Guidelines, design rule routing logic suitable for LLM execution, and continuously optimize and iterate to improve model performance and resource utilization efficiency.
- Establish an AI content quality management system, be responsible for quality results, and continuously conduct work such as problem diagnosis, data analysis, and model optimization.
Qualifications
Minimum Qualifications:
- Bachelor's degree or above, with 3+ years of experience in model operations, AI/ML operations, or related domains.
- Demonstrated ability to lead community policy development and collaborate effectively across Product, Engineering, and Operations teams. Strong problem-solving skills with the ability to identify root causes, prioritize initiatives, develop structured improvement roadmaps, drive execution, and measure impact through clear success metrics.
- Deep interest in internet products and strong awareness of AI industry trends. Familiarity with mainstream LLM products (e.g., ChatGPT, Gemini, etc.) and hands-on experience in model training, evaluation, or prompt engineering.
- Highly data-sensitive with strong analytical capabilities. Able to translate data insights into actionable strategies, synthesize complex findings, and proactively drive resolution of operational or model-related issues.
- Demonstrated understanding of community safety frameworks and risk governance. Strong risk awareness and accountability, with the ability to proactively identify content, model, or process risks and design scalable mitigation solutions.
Preferred Qualifications
- Background in product management or technical experience in search systems, artificial intelligence, or large language models are strongly preferred.
- Self-motivated and results-driven, able to influence stakeholders in fast-paced, ambiguous environments.
Responsibilities
ResponsibilitiesAbout the Team
The Platform Responsibility team is bringing disruptive innovation to content safety through the deep application of AI. We are building next-generation infrastructure that leverages advanced LLMs to reshape risk detection and governance. By engineering high-quality data pipelines and integrating AI into core decision-making, we drive exponential efficiency gains and precision. Working at the intersection of scalable engineering and technology, we empower global business growth while serving as the foundation of user trust.
About the Role
Under the spirit of TikTok Community Guidelines, the team leverages the capabilities of LLM and prompt engineering to deliver a large model Agent that can represent "absolute correctness", providing stable evaluation capabilities for TikTok content safety. This role will lead the team to refine strategy operations and prompt optimization to enhance the Agent's precise recall ability for risky content.
Responsibilities:
- Undertake AI special projects for product R&D, perform tasks such as annotation of the LLM model training data sample set, evaluation of model iteration effectiveness, industry application research, and security compliance assurance. Cooperate closely with upstream product technology to jointly promote the achievement of business objectives.
- Standardise Definitions: Responsible for the definition and access criteria of the Golden Set across all risk domains (pornography, violence and terrorism, politics-related, abuse, etc.). Convert qualitative Policy documents into quantitative annotation SOPs executable by the Data Ops team.
- Ground Truth Delivery: Responsible for key aspects of queue delivery, including but not limited to demand analysis, acceptance, solution customization and training, quality assurance, delivery, etc.
- Operation of the Adjudication Mechanism: Establish an adjudication mechanism for internal cases to align consistent judgments on risk issues of different levels.
- Based on an understanding of LLM content safety process design and Community Guidelines, design rule routing logic suitable for LLM execution, and continuously optimize and iterate to improve model performance and resource utilization efficiency.
- Establish an AI content quality management system, be responsible for quality results, and continuously conduct work such as problem diagnosis, data analysis, and model optimization.
Qualifications
QualificationsMinimum Qualifications:
- Bachelor's degree or above, with 3+ years of experience in model operations, AI/ML operations, or related domains.
- Demonstrated ability to lead community policy development and collaborate effectively across Product, Engineering, and Operations teams. Strong problem-solving skills with the ability to identify root causes, prioritize initiatives, develop structured improvement roadmaps, drive execution, and measure impact through clear success metrics.
- Deep interest in internet products and strong awareness of AI industry trends. Familiarity with mainstream LLM products (e.g., ChatGPT, Gemini, etc.) and hands-on experience in model training, evaluation, or prompt engineering.
- Highly data-sensitive with strong analytical capabilities. Able to translate data insights into actionable strategies, synthesize complex findings, and proactively drive resolution of operational or model-related issues.
- Demonstrated understanding of community safety frameworks and risk governance. Strong risk awareness and accountability, with the ability to proactively identify content, model, or process risks and design scalable mitigation solutions.
Preferred Qualifications
- Background in product management or technical experience in search systems, artificial intelligence, or large language models are strongly preferred.
- Self-motivated and results-driven, able to influence stakeholders in fast-paced, ambiguous environments.
Additional Information
- Job category: Operations
- Posted: Mar 23, 2026