Content Quality and Evaluation Team Lead - Eco & Social Creation

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.

What will I do?

As the Content Quality & Evaluation Team Lead, you will lead a team of Content Quality and Evaluation Specialist to build the Golden Sets that define Ground Truth for platform policies, AI model evaluation, and global enforcement teams. You will drive deep-dive analyses on high-risk and contentious safety cases, transforming macro policies into crystal-clear SOPs and operational guidelines. By orchestrating a continuous closed-loop feedback system across Operations, Algorithm, Product, and global teams, you will turn Golden Set insights into system-wide improvements—enhancing both human review quality and AI interception accuracy. You will also systematize quality methodologies, establish robust QA mechanisms, and own core data metrics.

Responsibilities

• Lead High Quality Datasets Production: Lead the team to produce high-quality datasets for model training and evaluation, curating long-tail, high-risk, and complex edge cases to establish accurate Ground Truth for policies, AI models, and global enforcement teams.
• Drive Deep-Dive & Process Abstraction: Oversee deep-dive analyses on high-risk and highly debated safety cases to identify misapplication patterns and risk trends, translating macro policies into logical SOPs and operational guidelines.
• Manage Quality Performance: Comprehensively manage quality performance across multiple workflows, drive continuous improvement, and ensure the achievement of both efficiency and quality goals.
• Lead Cross-Functional Collaboration: Lead collaboration with Operations, Algorithm, Product, and global teams to identify system vulnerabilities based on Golden Set metrics, achieving bidirectional improvements in human review quality and AI agent interception.
• Systematize QA Methodologies: Systematize universal methodologies for the content quality management framework and establish robust daily QA mechanisms, tracking core data metrics to enhance accuracy and operational efficiency.
• Proactively Identify & Mitigate Risks: Proactively identify quality risks and assess their impact on workflows, agilely resolving risks while ensuring stable delivery.
• Build Team Capability: Drive team capability building and operational management, including personnel development and resource allocation, to ensure

Minimum Qualifications

• Bachelor's degree or higher with at least 2 years of team management experience.
• Deep understanding of content safety policies and guidelines, with excellent content analysis, data analysis, and summarization skills.
• Strong English communication skills and logical thinking, with the ability to quickly understand business needs and effectively prioritize tasks.
• Strong leadership and operational management skills, familiarity with content quality control tools and management systems, and the ability to effectively motivate teams and handle unexpected situations.
• Experience managing cross-market teams or leading project implementation is preferred, with the ability to thrive in a fast-paced, multicultural environment.

Preferred Qualifications

• Proven experience in producing high-quality datasets for model training and evaluation, curating long-tail, high-risk, and complex edge cases to establish accurate Ground Truth for policies, AI models, and global enforcement teams.