AIGC Model Labelling Team Lead - Monetization Integrity

Responsibilities

Monetization Integrity Ops plays a critical role in supporting TikTok's Trust & Safety objectives. Our primary focus is on delivering high-quality content moderation at optimal cost, ensuring minimal exposure of both the platform and advertisers to high-risk content. From an advertiser's perspective, we are committed to driving consistency and accuracy in moderation outcomes, whether automated or human-led, so that brands can build trusted, long-term, and mutually beneficial commercial relationships with TikTok. Guided by the MI team's broader mission to make TikTok the world's most trusted ecosystem and the easiest platform to advertise on, our work contributes to TikTok's overall success in several key ways: - Enabling Growth: By creating a safe and reliable advertising environment that attracts and retains global partners. - Ensuring Compliance: By upholding moderation standards that align with legal, regulatory, and brand safety requirements. - Driving Innovation: By leveraging automation, data, and human expertise to continuously improve moderation outcomes. Responsibilities - Model Labelling Team Leadership & People Management - Lead, coach, and develop a team of model labelling specialists, fostering a high-performance and accountable culture - Set clear performance goals, conduct regular 1:1s, performance reviews, and career development planning - Manage capacity, workload allocation, and shift coverage to ensure consistent labelling output - Data-Driven Management & Analytics - Build and maintain model labelling scorecards, dashboards, and reporting cadences for leadership visibility - Quantify and report how the team's labelling output affects model training and evaluation outcomes - Translate insights into actionable improvement plans and influence prioritization decisions - Cross-Functional Collaboration - Partner with Automoderation, Product, Training, and WFM teams to drive model coverage and quality improvements and close feedback loops - Represent the model labelling function in governance forums and business reviews - Process Optimization & Continuous Improvement - Identify automation and tooling opportunities to scale model labelling efficiency and reduce manual effort - Champion a culture of continuous improvement, calibration, and operational excellence within the team

Qualifications

Minimum Qualifications: - Bachelor's degree or higher in Engineering, Business Analytics, Statistics, Information Management, or related fields - 5+ years of experience in Automation, Governance, Moderation, Operations Management, or related functions, with at least 1 year in a people management or team lead role - In-depth knowledge of large language model data production pipelines, including key stages and quality control points in "data collection/annotation — model training — model evaluation" - Solid data analysis skills to identify process issues and opportunities via insights; proficient with Data Visualization tools and Excel for analysis and retrospectives - 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 - Professional working proficiency in both Mandarin and English — required to work with Mandarin-language moderation guidelines and to collaborate daily with Mandarin-speaking stakeholders - Highly self-driven with a 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 - Experience with AI Agents, LLMs, or Prompt Engineering is a strong plus

Job Information