Explore the application and implementation of cutting-edge research such as large language models, graph neural networks, and multimodal techniques in financial risk scenarios.
Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
Support the development and ongoing enhancement of policies and procedures across the transaction monitoring lifecycle, including rule validation, system optimization, and underlying data analysis.
Construct multimodal semantic links across video-product, product-product, and video-video relationships to support trend understanding, product mining, AIGC generation, and content-commerce supply optimization.
Efficiency: Designing and implementing software platforms and monitoring frameworks for efficient, automated, and intelligent service-oriented architecture (SOA) governance.
Provide operational support for credit-bearing internship registration and documentation processes, including coordinating required submissions and liaising with relevant stakeholders.
Optimize system performance across latency, throughput, and cost dimensions by improving prompt chains and implementing scalable caching strategies for AI features serving large user bases.
AI scenarios: Participate in the application of AI in front-end development and core business scenarios, helping build an AI-driven R&D and system capability framework. This includes, but is not limited to, improving development efficiency through AI, such as code generation, workflow-driven development, and business understanding; participating in the design and practice of AI Native / Agentic Commerce capabilities, including interaction models and capability abstractions for agents; exploring and contributing to cutting-edge AI payment capabilities and industry-standard protocols; and promoting intelligent capabilities across payment and financial flows, such as decision intelligence, recommendation intelligence, and experience intelligence, to continuously improve engineering efficiency and business outcomes.
Support general annotation operation improvement initiatives across multiple data domains such as Reasoning, General Knowledge, STEM, and Humanities. Create and maintain technical guidelines and casebooks to support consistent and high-quality data production from external parties.