TikTok LIVE

Responsibilities The Livestream 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 with authors; it provides objective revenue to the platform and promotes content exclusivity. It also serves as a "new infrastructure" for expanding ecological boundaries. We are seeking a AI Data Operation Specialist to join our team to lead business operation initiatives in ecosystem and monetization governance—leveraging both human reviewing and machine learning models, including Large Language Models (LLMs). This role plays a critical part in upholding content diversity and revenue health across TikTok Live platform. The ideal candidate will be deeply involved in training AI models, analyzing content reviewing data to extract actionable insights, resolving complex content scenarios, and working closely with partner teams to ensure effective issue resolution. Success in this role requires strong analytical thinking, high ownership, and the ability to collaborate across cross-functional teams. A keen eye for detail and a proactive mindset toward challenging existing processes and driving continuous improvement are essential. Key Responsibilities Quality Operations & Process Excellence: Ensure consistent quality benchmarking, policy calibration, and performance analysis across partnership team Support onboarding, training, and operational readiness of new outsource teams in collaboration with cross-functional partners Lead and manage quality evaluation initiatives, generating insights and developing action plans to address performance gaps Handle content reviewing and analysis projects, delivering actionable trends and recommendations to project stakeholders Serve as custodian for quality-related documentation, including SOPs and reference materials, ensuring accuracy and accessibility Identify and implement process improvements, leveraging technology and collaboration to enhance quality and efficiency AI Operations – Model Training & Enhancement Train and fine-tune models using extensive labeled datasets to improve decision-making accuracy and overall performance Support iterative model improvement through reinforcement learning, testing, and data-driven adjustments Prepare, clean, and structure training data to ensure high-quality inputs for model development Collaborate with product teams and algorithm teams by providing examples and insights to identify and address potential gaps in model decision-making Draft, review, and quality-check training content to optimize the synergy between human inputs and AI data Design and craft high-quality, targeted prompts to test the limits and functionalities of AI models (e.g., language understanding, reasoning, creativity, and domain-specific tasks). Collaborate with cross-functional teams to understand business requirements and translate them into effective prompt strategies that align with product goals. Data Analysis & Reporting 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 Own and track all market specific KPIs and associated reports Representing quality insight and data for the specific market in timely reviews (WBR/MBR) and project connects Qualifications Minimum Qualifications: 1. Bachelor’s degree in Business, Data Science, Computer Science, Information Technology, Communications, or a related field; 2. 3+ years of experience in AI data operation, leveraging AI and ML for content quality management, product operations, or a related analytics role, preferably in tech, digital content, or platform moderation environments; 3. Proficiency in data analysis and visualization tools such as Excel, Tableau, Power BI, or similar skills; 4. Basic understanding of machine learning concepts and Large Language Models (LLMs); 5. Familiarity with dashboard creation and documentation tools. Strong ability to analyze complex datasets, identify patterns, and generate actionable insights; 6. Strong critical thinking and problem-solving skills, with a proactive approach to identifying and driving process improvements. Preferred Qualifications: 1. Able to review and analyze potentially sensitive or disturbing content with objectivity, professionalism, and emotional resilience; 2. Strong analytical skills with the ability to translate data into actionable insights, influence strategy, and drive impactful solutions; 3. Highly adaptable, proactive, and self-motivated, with a proven ability to thrive in fast-paced and constantly evolving environments; 4. Solid understanding of machine learning principles, including model evaluation metrics and optimization techniques; 5. A deep interest in LLMs, human behavior and user experience is essential. The ideal candidate is an enthusiastic learner who finds engagement with diverse case studies and annotators stimulating; 6. Experience as RLHF (Reinforcement learning from human feedback) annotators for leading AI/LLM companies is strongly preferred. #J-18808-Ljbffr