Backend Engineer Graduate (ByteRec Recommendation Infrastructure) - 2026 Start (BS/MS)

About the Team

The ByteRec (Recommendation Architecture Middle-Platform) Team is responsible for system architecture design in the fields of content understanding and content security for products. The scope of work includes the design and development of the entire process of massive multi-modal content processing, retrieval, RAG, and sorting, ensuring the high availability of the system, and pursuing flexible abstraction and sustainable iteration. We also maintain VikingDB as a cloud-native RAG service.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok. Successful candidates must be able to commit to an onboarding date by end of year 2026. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

• Be responsible for the service construction and iteration of the multi-modal content understanding pipeline, solve core problems such as service availability, throughput and storage bottlenecks, and improve the development efficiency of new features. - Regarding the repetition and similarity issues of massive video content, closely collaborate with the algorithm team to continuously promote the application of industry-leading video representation models and large-scale vector retrieval technologies at the business level, and overcome engineering problems during the implementation process. - Abstract and enrich the multi-modal vector computing components, optimize the model inference performance of vector computing, enhance the stability, performance, and scalability of the system, and strengthen platform-wide integration.