Machine Learning Engineer Intern – Content Recommendation Systems

Job Description

Machine Learning Engineer Intern (Global E-Commerce Content Recommendation) – 2026 Summer (BS/MS) | TikTok

The Tone:
This is an internship at TikTok, likely located in Los Angeles, CA. TikTok builds the leading destination for short-form mobile video, aiming to inspire creativity and bring joy to its global community. This role is central to the company, driving critical product decisions and platform growth by developing and innovating on production recommendation models. The internship offers students industry exposure and hands-on experience, supporting personal and professional growth within a collaborative, impact-driven environment.

The TL;DR
• Role: Internship
• Type: Seasonal
• Location: In-person, Los Angeles, CA
• Pay: $45–$60 hourly
• Team: Global E-Commerce Content Recommendation team, made up of machine learning researchers and engineers.
• Mission: To support and innovate on production recommendation models that drive product impact and elevate the user experience in global e-commerce.
• Tech Stack: PyTorch, TensorFlow, C/C++, Python, shell programming

What You’ll Actually Do
• Drive the development of industry-leading recommendation systems to enhance user experience, strengthen platform safety, and empower the content ecosystem.
• Explore generative recommendation techniques, including Diffusion Models, prompt learning, and multimodal content generation, to unlock new capabilities in content discovery.
• Build multi-model and cross-scenario systems that enable unified recommendation across livestreams, short videos, and search functionalities.
• Deliver impactful, end-to-end machine learning solutions addressing high-priority product challenges related to content understanding, Large Language Models (LLMs), robustness, and fairness.
• Own and optimize the full-stack ML pipeline, from algorithm design to system infrastructure, to continuously improve recommendation performance.

The Must-Haves
• Background: Currently pursuing a Bachelor’s or Master’s degree in computer science, machine learning, or similar fields.
• Experience: Good knowledge of theoretical and empirical research in addressing research problems; able to commit to working for 12 weeks during Summer 2026.
• 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 AI conferences or journals; proficient in C/C++, Python, and shell programming languages, with a deep understanding of data structure and algorithm design; internship experience in an AI research organization.