Responsibilities - Evolve TikTok's AI Search multi-agent LLM engine, supporting ReAct + Tool calling, DAG-based workflows, and RAG paradigms - Deploy and optimize text/multimodal LLMs, including inference acceleration, model alignment during training, and reinforcement learning - Build scalable and reliable end-to-end serving platforms supporting multiple TikTok AI Search use cases, such as Q&A cards, in-app chatbot, and visual search, including both online and offline scenarios - Build large-scale data architecture for handling billion-level data records: offline computation, distributed system performance and scheduling optimization, as well as building high-availability, high-throughput, and low-latency online services - Design and build personalized AI search capabilities to achieve more accurate AI Overview and Q&A experience for users - Collaborate with modeling and product teams to deliver better AI search experience for Tiktok users . - Effective communication and teamwork skills, strong ownership mindset Preferred Qualifications: - Familiar with system performance optimization in Linux environment, experience with large-scale C++ system development are preferred - Familiar with large-scale distributed systems development; experience with distributed databases or distributed data processing frameworks is a plus - Experience with GPU inference optimization, LLM/VLM serving and training are preferred .