Machine Learning Engineer Intern – Recommendation Systems

Job Description

Machine Learning Engineer Intern (Recommendation) – 2026 Summer (BS/MS) | TikTok

The Tone:
This is an internship at TikTok, with opportunities likely available in various US locations. TikTok is the leading global destination for short-form mobile video, committed to inspiring creativity and bringing joy through its innovative product. This role within the recommendation algorithm team is central to the company, driving critical product decisions and platform growth. Interns will contribute to developing industry-leading recommendation systems that enhance user experience, strengthen platform safety, and empower a vibrant content ecosystem.

The TL;DR
• Role: Internship
• Type: Temporary
• Location: Variable (US)
• Pay: $45 hourly
• Team: Recommendation algorithm team, composed of machine learning researchers and engineers
• Mission: Drive the development of industry-leading recommendation systems that elevate user experience, strengthen platform safety, and empower a vibrant content ecosystem.
• Tech Stack: PyTorch, TensorFlow, C/C++, Python, shell programming languages

What You’ll Actually Do
• Develop: Drive the creation of industry-leading recommendation systems to enhance user experience, strengthen platform safety, and empower a vibrant content ecosystem.
• Deliver: Provide impactful, end-to-end machine learning solutions that address high-priority product challenges related to content understanding, LLMs, robustness, and fairness.
• Optimize: Own and refine the full-stack ML pipeline, from algorithm design to system infrastructure, to continuously improve recommendation performance.
• Collaborate: Work with cross-functional teams to devise innovative product strategies and develop intelligent solutions that support TikTok’s growth in key global markets.

The Must-Haves
• Background: Currently pursuing a Master’s degree in computer science, machine learning, or similar fields, and able to commit to working for 12 weeks during Summer 2026.
• Experience: Good knowledge of theoretical and empirical research for 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.
• Bonus: Research experience in applied machine learning, machine learning infrastructure, large-scale recommendation systems, or market-facing machine learning products; strong first-author publications record in top AI conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, EMNLP, NAACL); proficiency in C/C++, Python, and shell programming languages, with a deep understanding of data structure and algorithm design; prior internship experience in an AI research organization.