Machine Learning Engineer Intern (Global E-Commerce, Search) - 2027 Start

About the Team Our team is responsible for the search algorithm for our rapidly growing global e-commerce business. We use state-of-the-art large-scale machine learning technology, the cutting-edge NLP, CV and multi-modal technology to build the industry's top-class search engine to provide the best e-commerce search experience, for more than 1 billion monthly users around the world. Our mission is to build a world where "there is no hard-to-sell good-priced product in the world".

We are looking for talented individuals to join us for an internship. Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals. Candidates may apply to a maximum of two positions across Our Company and its affiliates globally. Applications will be considered in the order they are submitted. Applications are reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume, including your start and end dates.

Responsibilities 1. Improve the basic search quality and user experience: Optimize query analysis and text relevance matching. Understand e-commerce video content and implement multi-modal matching. Improve users' perception of product authority, and deeply participate in the design and implementation of core search products. Comprehensively improve the end-to-end shopping experience from browsing to after-sales. 2. Design and implement the end-to-end ranking system (recall, first stage ranking, final stage ranking and mixed row): Improve users' personalized shopping interests model. Improve the shopping conversion efficiency for merchandise, video and live stream to promote GMV growth. 3. Promote the development of the ecosystem: From the perspective of the industry and businesses, solve challenging problems such as supply and demand matching, business cold start, and sustainable business growth, etc. Think, analyze and adjust the evolution of the system to achieve long-term and sustainable growth of GMV. 4. Participate in the exploration and development of personalized AI search, with a focus on harness engineering, post-training optimization, and rubric-based automated evaluation, to build next-generation search experiences that better understand users, reason over intent, and make intelligent decisions. 5. Work in a team setting and apply knowledge in statistics, scripting and programming languages required by the firm. 6. Work with the relevant software platforms in which the models are deployed.