PhD Intern – Recommendation Algorithms

Job Description

Machine Learning Scientist Intern (TikTok-Recommendation) – 2026 Start (PhD) | TikTok

The Tone:
This is a PhD internship at TikTok, a company that operates the leading destination for short-form mobile video. The role is part of the central recommendation algorithm team, which drives critical product decisions and platform growth. This position offers students the opportunity to actively contribute to TikTok’s products and research, influencing the organization’s future plans and emerging technologies.

The TL;DR
• Role: Internship
• Location: Varies; potentially in-person or remote
• Pay: $60 hourly
• Team: Recommendation algorithm team, made up of machine learning researchers and engineers
• Mission: To develop industry-leading recommendation systems that enhance user experience, platform safety, and content ecosystems.
• Tech Stack: PyTorch, TensorFlow, C/C++, Python, shell programming languages

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

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.
• 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; deep understanding of data structure and algorithm design.
• Bonus: Research experience in applied machine learning, machine learning infrastructure, large-scale recommendation system, or market-facing machine learning products; strong first-author publications record in accredited AI conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL etc.); internship experience in an AI research organization.