Algorithm Engineer Intern (Global Live - Strategy) - 2026 Start (PhD)

in a higher ROI operation for both LIVE streamer and watcher;
3. Make detailed analysis on user data and system data to find out user experience optimiaztion zoom;
4. Other work like user growth strategy, cold-start strategy, etc.

We are looking for talented individuals to join us for an internship in 2026. PhD Internships at TikTok aim to provide students with the opportunity to actively contribute to our products and research, and to the organization's future plans and emerging technologies.

Job Description

1. Participate in the optimization of ByteDance LIVE monetization business and serve the LIVE experience of billions of global users;
2. Adopt cutting-edge machine learning model to scientifically model massive user behaviour and consumption data, build high-performance/high-reliability architecture services, and bring users the ultimate experience in LIVE consumption;
3. Deeply participate in product/business discussions, fully analyze and understand user behaviour patterns, and provide optimization directions for the overall business.

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.

Successful candidates must be able to commit to either of the following Internships

• From January to June
• From May to August (Summer)

Qualifications

Minimum Qualifications

1. Currently pursuing a PhD in Computer Science, engineering quantitative field
2. Familiar with C/C++/ Python development, familiar with Linux multi-threaded /multi-process;
3. Familiar with commonly used machine learning and deep learning algorithms, including but not limited to boost machine, dnn, reinforcement learning, etc.;
4. Solid maths foundation, including probability statistics, numerical optimization, etc., sensitive to data, good at discovering, analyzing and solving problems from data;
5. Familiar with at least one of Flink, Spark, Hive etc., with big data parallel processing experience;

Preferred Qualification

• Experience in large-scale recommend/advertising systems, risk control systems or LLM is preferred

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

If you have any questions, please reach out to us at [email protected]