Big Data Engineer Intern (TikTok Recommendation Architecture) - 2026 Start (BS/MS)

Team Introduction
Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation system to provide the most stable and best experience for our TikTok users. The team is responsible for system stability and high availability, online services and offline data flow performance optimization, solving system bottlenecks, reducing cost overhead, building data and service mid-platform, realizing flexible and scalable high-performance storage and computing systems.

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 reasonable offline data architecture for large-scale recommendation systems.
- Design and implement flexible, scalable, stable and high-performance storage and computing systems.
- Trouble-shooting of the production system, designing and implementing the necessary mechanisms and tools to ensure the stability of the overall operation of the production system.
- Build industry-leading distributed systems such as storage and computing to provide reliable infrastructure for massive data and large-scale business systems.
- Develop and implement techniques and analytics applications to transform raw data into meaningful information using data-oriented programming languages and visualisation software.
- Apply data mining, data modeling, natural language processing, and machine learning to extract and analyse information from large structured and unstructured datasets.
- Visualise, interpret, and report data findings and may create dynamic data reports as well.