Software Engineer – Global E-Commerce Search Infrastructure (TikTok Shop)

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.

Responsibilities: You will design, build, and optimize the core infrastructure that supports TikTok Shop’s recall, ranking, and re-ranking pipelines globally.

• Core Search Engine Development: Design and implement high-performance online retrieval systems. Optimize core components including the inverted index, vector retrieval (ANN/HNSW), query understanding, and merger logic.
• Real-Time 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 Stability & Performance: Drive latency, throughput, and cost optimizations for services handling hundreds of thousands of QPS. Troubleshoot complex distributed system issues, manage cross-region failover, and design high-availability disaster recovery solutions.
• Large-Scale Storage & Retrieval: Design and optimize distributed storage libraries (based on RocksDB/Redis) and columnar databases tailored for high-speed e-commerce feature retrieval.
• ML Infrastructure Collaboration: Work closely with Algorithm/ML Engineers to productionize state-of-the-art Large Language Models (LLMs) , AI Search, and multi-modal search models, ensuring the infrastructure supports massive model serving and real-time feature engineering.

Minimum Qualifications:

• Bachelor’s in Computer Science, Computer Engineering, or a related technical field.
• At least 3 years of hands-on experience building large-scale distributed systems, search engines, or low-latency online services.
• Strong coding proficiency in C++, Go, or Java (C++/Go is heavily preferred for core infra roles).
• Deep understanding of computer science fundamentals: Data structures, algorithms, operating systems, network programming, and multi-threading.
• Experience with distributed system technologies, such as RPC frameworks (gRPC/Thrift), Message Queues (Kafka), and Stream Processing (Flink/Spark).

Preferred Qualifications:

• Search Internals: Direct experience with search engine internals (e.g., Lucene, Elasticsearch, Solr, Vespa) or building custom inverted index/retrieval systems.
• Vector Search: Experience with vector database technologies or libraries (FAISS, HNSW, ScaNN).
• Storage Engines: Deep understanding of NoSQL and KV stores (Redis, RocksDB, HBase) or columnar storage systems.
• Performance Optimization: Proven track record of reducing p99 latency, optimizing memory usage in C++, or driving measurable efficiency gains in high-traffic systems.
• Domain Knowledge: Experience working in E-commerce, AdTech, or large-scale consumer platforms.