Software Engineer Intern; Recommendation Infrastructure - Summer; Bachelor/Master
Job in
San Jose, Santa Clara County, California, 95111, USA
Listed on 2026-02-17
Listing for:
Tiktok
Seasonal/Temporary, Apprenticeship/Internship
position Listed on 2026-02-17
Job specializations:
-
Software Development
AI Engineer, Machine Learning/ ML Engineer, Data Scientist
Job Description & How to Apply Below
Our Recommendation Architecture Team is responsible for building up and optimizing the architecture for our recommendation products to provide the most reliable and best experience for our Tik Tok users. Interns are important parts to our team with your fresh ideas and creative thoughts.
We are looking for talented individuals to join us for an internship in 2026. Internships at Tik Tok aim to offer students industry exposure and hands-on experience. Turn your ambitions into reality as your inspiration brings infinite opportunities at Tik Tok.
Internships at Tik Tok aim to provide students with hands-on experience in developing fundamental skills and exploring potential career paths. A vibrant blend of social events and enriching development workshops will be available for you to explore. Here, you will utilize your knowledge in real-world scenarios while laying a strong foundation for personal and professional growth. It runs for 12 weeks.
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 Tik Tok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis. We encourage you to apply as early as possible. Please state your availability clearly in your resume (Start date, End date).
Summer Start Dates:
* May 11th, 2026
* May 18th, 2026
* May 26th, 2026
* June 8th, 2026
* June 22nd, 2026
Responsibilities
* Build and maintain high performance online services for Tik Tok recommendation system to support various types of products, such as For You Feed, E-commerce, Social, etc.
* Build extremely efficient and reliable data pipelines for candidates generation, profile generation, training examples generation, realtime online training, etc;
* Build globalized large-scale recommendation system;
* Design and develop high performance computing frameworks and storage systems.
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