Job Description

Team Introduction

TikTok's Recommendation Architecture Team is responsible for designing and developing the architecture and computing systems that power the recommendation engines behind products with over a billion users. The team ensures system stability and high availability, abstracts general-purpose real-time and batch computing frameworks, and builds flexible, scalable, high-performance storage systems and computing models. We provide core infrastructure and general-purpose components for key areas such as deduplication, counting, feature generation, training pipelines, and stream-batch computing engines, enabling the success of recommendation services at scale.

For roles looking to start before calendar year 2026 : We are looking for talented individuals to join us for an internship in from Sept. 2025 onwards. Internships at TikTok aim to offer students industry exposure and hands-on experience. Watch your ambitions become reality as your inspiration brings infinite opportunities at TikTok.

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.

Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities

- Design and implement scalable distributed computing and training systems for large-scale recommendation systems.

- Build flexible, extensible, stable, and high-performance components for offline storage, computing, and training.

- Perform troubleshooting for production systems, and design and develop tools and mechanisms to ensure system stability and reliability.

- Develop industry-leading distributed training and computing frameworks for recommendation systems, providing robust infrastructure for massive datasets and large-scale business systems.