
TikTok LIVE - AI Data Operation Specialist
- London
- Permanent
- Full-time
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 efficiencyAI 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 connectsQualifications:Minimum Qualifications:
- Bachelor's degree in Business, Data Science, Computer Science, Information Technology, Communications, or a related field
- 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
- Proficiency in data analysis and visualization tools such as Excel, Tableau, Power BI, or similar
- Basic understanding of machine learning concepts and Large Language Models (LLMs)
- Familiarity with dashboard creation and documentation tools
- Strong ability to analyze complex datasets, identify patterns, and generate actionable insights
- Strong critical thinking and problem-solving skills, with a proactive approach to identifying and driving process improvementsPreferred Qualifications:
- Able to review and analyze potentially sensitive or disturbing content with objectivity, professionalism, and emotional resilience
- Strong analytical skills with the ability to translate data into actionable insights, influence strategy, and drive impactful solutions
- Highly adaptable, proactive, and self-motivated, with a proven ability to thrive in fast-paced and constantly evolving environments
- Solid understanding of machine learning principles, including model evaluation metrics and optimization techniques
- 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
- Experience as RLHF (Reinforcement learning from human feedback) annotators for leading Al/LLM companies is strongly preferred
- Strong analytical skills with the ability to translate data into actionable insights, influence strategy, and drive impactful solutions.
- Solid understanding of machine learning principles, including model evaluation metrics and optimization techniques.
- Experience as RLHF (Reinforcement learning from human feedback) annotators for leading Al/LLM companies is strongly preferred.