AI Data Operation Specialist Graduate (TikTok LIVE) - 2027 Start

About Our Team TikTok LIVE Team is committed to creating real-time interactive scenes. As a new form of content, livestream creates value for all parties in the ecology. Livestream provides users with a unique consumption experience and further generalizes content. It is also a new way of employment to provide more direct fan interaction and deepen relationships to authors; It provides robust and objective revenue to the platform and promotes content exclusivity. It also serves as a "new infrastructure" for the expansion of ecological boundaries.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities: 1. Ensure high-quality content benchmarking across BPO teams, support the setup, onboarding, and training of new BPO teams. Manage policy clarifications, calibrations, and arbitration processes. Analyze BPO team performance to identify knowledge gaps and systemic issues. 2. Handle content labeling for specific queues based on cross-functional business requirements, analyze labeled content to identify trends and provide insights to project teams and independently manage quality evaluation initiatives, delivering actionable analytical insights. 3. Train models using large datasets of labeled content to improve decision-making accuracy. Enhance model capabilities through iterative training and reinforcement learning, assist in data preparation, cleaning, and structuring for training purposes. Improve model accuracy by testing and fine-tuning, highlight the algorithm team with supporting examples for any potential gaps in LLM decision making draft, revise, and quality-check content to explore and enhance the synergy between human input and data in LLM training. 4. Analyze moderation and labeling data from multiple queues to derive a process or market specific trend/correlation. Arrange supporting data points for impact analysis and solution planning. 5. Custodian of all quality specific artifacts for the content moderation scope, generating creative solutions, including the use of technology and tools, to enhance the quality of both individual and team outputs.