软件工程师项目实习生 - 2026年入职

About the Team: Search is no longer just a feature—it is the defining battleground that will determine whether TikTok Shop becomes the first truly global e-commerce super-app. Our Search platform is the core engine behind the "shelf-field" (product card) strategy, and the key to competing head-to-head with Amazon, Taobao, and Pinduoduo in a global market worth over $10 trillion. Search will propel TikTok Shop from tens of billions to hundreds of billions in annual GMV by activating real shopping intent, unlocking zero-sales products, and ensuring every item becomes instantly discoverable the moment a user types or taps. We innovate where extreme performance, massive global scale, and uncompromising consistency meet. As a Project Intern, you will contribute to impactful short-term projects and gain hands-on experience in a fast-paced, professional environment. This internship offers the opportunity to develop practical skills, apply your knowledge to real-world challenges, and explore your career interests. Applications are reviewed on a rolling basis, so we encourage you to apply early. Responsibilities: During this internship, you will join the E-Commerce Engineering team to tackle challenges in distributed systems and information retrieval. You will: - Core Architecture: Design and develop high-performance, low-latency, and high-availability online search services. Optimize core components including the inverted index, vector retrieval (ANN/HNSW), and query understanding. - Data Pipelines: Build highly scalable and fault-tolerant data pipelines using Flink, Kafka, and Spark to ensure product changes (price, stock, and new listings) are reflected in search results in near real-time. - System Optimization: Drive latency and throughput optimizations for services handling hundreds of thousands of QPS. Troubleshoot complex distributed system issues to ensure 99.99% availability. - Innovation: Participate in the research and implementation of next-generation search infrastructure, focusing on storage decoupling, cloud-native architecture, AI Search, and multi-modal fusion. - Collaboration: Work with your mentor and ML engineers to productionize state-of-the-art models and build globalized large-scale recommendation systems.