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

About the Team

The Recommendation Architecture Team is responsible for designing and developing recommendation system architectures for various products under the company. We ensure system stability and high availability, optimize performance for online services and offline data pipelines, address system bottlenecks, and reduce operational costs. We also abstract reusable system components and services to build recommendation and data middleware platforms, supporting rapid incubation of new products and empowering enterprise clients (ToB).

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

• Design intelligent development toolkits for large-scale recommendation systems, providing tooling and productized solutions to enhance R&D efficiency. - Develop business metrics-driven gray release systems to ensure safe, stable, and efficient release strategies and workflows. - Enhance observability of recommendation systems in complex global environments (multi-region, multi-data center, multi-language), establish end-to-end tracing systems, and optimize issue attribution mechanisms. - Build algorithm engineering toolchains to accelerate the end-to-end process from experimental algorithm/model development to deployment, improving iteration efficiency. - Overhaul platform ecosystem architectures and develop data intelligence assistants.