Machine Learning Scientist Intern (TikTok-Recommendation) - 2027 Start (PhD)

About the Team Recommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies. Our dynamic internship experience blends hands-on learning, enriching community-building and professional development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).

In this role, you'll have the opportunity to: - Drive the development of industry-leading recommendation systems that elevate user experience, strengthen platform safety, and empower a vibrant content ecosystem. - Deliver impactful, end-to-end machine learning solutions that tackle high-priority product challenges related to content understanding, LLMs, robustness, and fairness. - Own and optimize the full-stack ML pipeline—from algorithm design to system infrastructure—to continuously push the boundaries of recommendation performance. - Collaborate with cross-functional teams to craft innovative product strategies and develop intelligent solutions that fuel TikTok’s growth in key global markets.

Minimum Qualifications: - Currently pursuing a PhD with a background in computer science, machine learning, or similar fields; - Good knowledge of theoretical and empirical research in addressing research problems; - Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch,TensorFlow) and familiarity with deep neural network architectures.

Preferred Qualifications: - Research experience in one or more of the following fields: applied machine learning, machine learning infrastructure, large-scale recommendation system, market-facing machine learning product; - Strong first-author publications record in top AI conferences or journals(e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.); - Proficient in C/C++, Python, and shell programming languages, and have a deep understanding of data structure and algorithm design; - Internship experience in an AI research organization.