Machine Learning Researcher Intern – Content Recommendation

Job Description

Machine Learning Scientist Intern (Global E-Commerce Content Recommendation) – 2026 Summer (PhD) | TikTok

The Tone:
This is a PhD internship at TikTok, with a global presence, located in Los Angeles, CA. TikTok builds a leading destination for short-form mobile video, aiming to inspire creativity and bring joy to its users. This role is central to driving critical product decisions, platform growth, and innovating on production recommendation models within the global e-commerce team. The internship provides an opportunity to contribute actively to the company’s products, research, and emerging technologies.

The TL;DR
• Role: Internship
• Location: In-person, Los Angeles, CA
• Pay: $57 hourly
• Team: Global E-Commerce Content Recommendation team, made up of machine learning researchers and engineers.
• Mission: This person drives critical product decisions, platform growth, and innovates on production recommendation models for global e-commerce.
• Tech Stack: PyTorch, TensorFlow, C/C++, Python, shell programming languages

What You’ll Actually Do
• Build: Build industry-leading recommendation systems to improve user experience, content ecosystem, and platform security.
• Explore: Explore generative recommendation techniques, including Diffusion Models, prompt learning, and multimodal content generation, to unlock new capabilities in content discovery.
• Construct: Construct multi-model and cross-scenario systems that enable unified recommendation across livestreams, short videos, and search.
• Deliver: Deliver end-to-end machine learning solutions to address critical product challenges.
• Optimize: Own the full-stack machine learning system and optimize algorithms and infrastructure to improve recommendation performance.

The Must-Haves
• Background: Currently pursuing a PhD with a background in computer science, machine learning, or similar fields.
• Experience: Good knowledge of theoretical and empirical research in addressing research problems. Preferred qualifications include research experience in applied machine learning, machine learning infrastructure, large-scale recommendation systems, or market-facing machine learning products, along with internship experience in an AI research organization.
• Skills: Solid knowledge and experience with at least one popular deep learning framework (e.g., PyTorch, TensorFlow) and familiarity with deep neural network architectures. Proficient in C/C++, Python, and shell programming languages, with a deep understanding of data structure and algorithm design.
• Bonus: Strong first-author publications record in top AI conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.).