Research Scientist Intern (TikTok-Recommendation) - 2027 Start (PhD)

About the role

The Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team consists of machine learning researchers and engineers who support and innovate on production recommendation models, driving product impact. This internship provides PhD students the opportunity to actively contribute to products and research, blending hands-on learning, professional development, and collaboration with industry experts.

Responsibilities

• Build industry-leading recommendation systems, improving user experience, content ecosystem, and platform security.
• Deliver end-to-end machine learning solutions to address critical product challenges.
• Own the full-stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.
• Work with cross-functional teams to design product strategies and build solutions to grow TikTok in important markets.

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD degree in computer science or a related technical discipline.
• Proficient coding skills and strong algorithm & data structure knowledge using C++/Python or other programming languages.
• Experience in Machine Learning, familiar with at least one Deep Learning framework (e.g., PyTorch, TensorFlow).
• Experience in one or more of the following areas: NLP, CV, Recommender Systems, or Machine Learning.
• Effective communication and teamwork skills.

Preferred Qualifications:

• Authors of published papers in top academic conferences.
• Winners of algorithm and machine learning competitions such as ACM and Kaggle.

Benefits

• Day-one access to health insurance, life insurance, and wellbeing benefits.
• 10 paid holidays per year and paid sick time (56 hours if hired in the first half of the year, 40 if hired in the second half).
• Eligibility for housing allowance (for non-remote interns).

Pay

The hourly rate range for this position is $60–$60.