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.
Provide operational support for credit-bearing internship registration and documentation processes, including coordinating required submissions and liaising with relevant stakeholders.
Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the e-commerce community.
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.
Efficiency: Designing and implementing software platforms and monitoring frameworks for efficient, automated, and intelligent service-oriented architecture (SOA) governance.
Collaborate with cross-functional teams, including all three lines of defence, for in-depth data-driven risk advisory support, process enhancement initiatives, and root cause analysis for fraud prevention.
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.
AI scenarios: Participate in the application of AI in client-side 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.
Establish and maintain strong relationships with external vendors and partners, ensuring timely delivery, quality control, and effective communication.
Security Engineering & AI – Explore and develop AI-powered solutions for security engineering, including vulnerability discovery, security analysis, code review, and security automation.