About the job
The TikTok Search team is responsible for delivering a world-class search experience across TikTok’s global ecosystem. Our mission is to connect users with the most relevant and high-quality content through advanced technologies in search ranking, recommendation, and multimodal understanding. As a campus hire, you will collaborate with top engineers and researchers to solve challenging problems at scale, working across the full stack of search—from content understanding and retrieval to ranking and user experience optimization.
Responsibilities
Develop next-generation AI search systems using large models (LLMs).
Improve ranking, personalization, and relevance in search.
Build generative and multimodal search models (video, text, image).
Explore LLM-based agents for complex and multi-turn queries.
Optimize large-scale retrieval and ranking performance.
Collaborate cross-functionally to ship research into production.
Qualifications
Minimum
Individuals who are completing or recently completed a PhD in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
Solid foundation in machine learning, deep learning, or information retrieval.
Experience in at least one of the following areas: LLMs, search/recommendation systems, ranking, NLP, or multimodal learning.
Strong programming skills in Python and familiarity with ML frameworks (e.g., PyTorch, TensorFlow).
Demonstrated research ability through publications, projects, or internships.
Strong problem-solving skills and ability to work in a fast-paced, collaborative environment.
Preferred
Track record of research contributions through publications, open-source projects, or impactful research work.
Hands-on experience with large-scale systems, distributed training, or real-world ML deployment.
Experience with search, recommendation, or ads ranking systems in industry or research.
Experience with multimodal models (video, image, text) or generative AI applications.
Familiarity with LLM fine-tuning, alignment (e.g., RLHF), or agent-based systems.
Strong interest in building end-to-end AI systems from modeling to production.
Internship or research experience at leading technology companies or research organizations.
Modeling experience in one or more of the following areas: Ads, Search engine, Recommender System, NLP/CV.
Have a solid foundation in algorithms related to LLMs, including but not limited to comprehensive learning and practical experience in areas such as single-modal/multi-modal LLM application and deployment.
Strong publications record in accredited conferences or journals（e.g., ICLR, NeurIPS, ICML, ACL, EMNLP, NAACL, CVPR, ICCV and ECCV）.