Team Introduction The AI Data and Safety team plays a critical role in advancing Seed foundational models across modalities and improving AI-native applications built on the Seed model series. We work across the data lifecycle, from defining evaluation approaches and translating user feedback and benchmark outcomes into data requests, to building scalable processes that improve data quality and support rapid model iteration. Our team combines technical and operational capabilities, bringing together multidisciplinary talent across product management, data engineering, and data operations. Our work is driven by people who think deeply about model behavior, move quickly to solve complex problems, and bring first-hand experience as both builders and users of models and agents. In close partnership with Seed researchers, industry experts, and leading data vendors, we tackle challenging data problems at the frontier of AI development, helping improve both model performance and user experience. AI Data & Safety - External Partnership Development Team is dedicated to continuously sourcing high-quality data suppliers for foundation models and AI-native applications. Based on the data requirements of model training, the team conducts market research and manages the end-to-end process—from supplier sourcing and evaluation, commercial negotiations, and project initiation, to final delivery. By efficiently fulfilling data requests and building a robust supplier ecosystem, the team provides a reliable, high-quality data foundation for the continuous iteration of our models. AI Training Data Market Research and Resource Development 1. Partner closely with AI model training teams to understand business needs, define data types, standards, and core requirements, and conduct structured industry and market research to stay abreast of AI data trends, market landscape, and technological advancements 2. Translate market insights into high-quality data resource development strategies by