Content Quality and Evaluation Specialist - AI Data Service Operations

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.

Key Responsibilities - Develop, refine, and maintain Operational Guidelines for assigned policy areas, translating policy intent into clear, actionable instructions and ensuring alignment with policy changes, platform updates, and operational best practices. - Produce, validate, and maintain high-quality Testing Sets for calibration, QA evaluation, arbitration, and operational assessments, ensuring balanced coverage of scenarios, content types, and edge cases. - Analyze complex, ambiguous, and high-risk cases to provide structured clarifications, reduce enforcement discrepancies, and inform OG and Testing Set improvements. - Support arbitration, QA, training, and calibration workflows by identifying misapplication patterns and operational gaps, driving measurable improvements in reviewer accuracy and consistency. - Collaborate cross-functionally with Policy, Governance, Product, Engineering, Algo, and Training teams to ensure OGs and Testing Sets are scalable, actionable, and effectively translated into SOPs and training materials. - Track quality and operational metrics to identify improvement opportunities and drive continuous enhancements in enforcement accuracy, workflow efficiency, and cross-team effectiveness. - Contribute to ad-hoc quality and governance initiatives that enhance enforcement quality, operational effectiveness, and team performance.

Minimum Qualifications - Bachelor’s degree in Social Sciences, Arts & Humanities, or a related field. - Proficient in English as a primary working language, with strong attention to detail, clarity, and linguistic consistency, plus strong written communication skills that help turn complex ideas into practical guidance. - Internship, academic project, campus organization, or full-time experience in quality assurance, training, editorial review, operations, or a related field is valuable. - Demonstrated ability to interpret and apply complex guidelines or policies in writing-focused workflows, and some experience evaluating qualitative content or using data to improve processes. Internship, research, and project experience all count. - Ability to design and deliver interactive, engaging training materials or learning sessions, whether through internships, campus activities, project work, or full-time experience.

Preferred Qualifications - Additional experience with content moderation policy, operational guideline development, or enforcement workflows. - A self-starter mindset, solution-oriented thinking, and the ability to manage multiple priorities in a fast-paced, collaborative environment. - Familiarity with machine-executable logic, labeling frameworks, or test-set workflows. - Experience collaborating with Policy, Product, Governance, Engineering, or Training teams through internships, projects, research, or full-time roles. - Knowledge of scenario coverage, positive/negative balance, and dataset validation. - Excitement to learn quickly, grow with feedback, and build strong cross-functional judgment early in your career. - Strong interest in policy, content moderation, quality operations, or related work. Prior exposure through internships, research, projects, or student activities is a plus. - Familiarity with content moderation policy, operational guideline development, or enforcement workflows through coursework, internships, research, or project work is a plus.