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

About the Team
Our Recommendation Architecture Team is responsible for building and optimizing the architecture of the recommendation system to provide the most stable and best experience for TikTok users. The team focuses on optimizing the recommendation system architecture, ensuring stability and high availability, and improving the performance of both online services and offline data flows. Collaborating with the algorithm team, we work to enhance recommendation effectiveness and user experience, boost system performance while reducing costs, build data and service mid-platforms, and realize flexible and scalable high-performance storage and computing systems.

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 and implement reasonable offline data architecture for large-scale recommendation systems.
- Design and implement flexible, scalable, and high-performance storage and computing systems.
- Trouble-shooting of the production system, design and implement 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 visualization software.
- Apply data mining, data modeling, natural language processing, and machine learning to extract and analyze information from large structured and unstructured datasets.
- Visualize, interpret, and report data findings and may create data reports as well.