Machine Learning Engineer Intern (E-Commerce Recommendation Video) - 2027 Start (PhD）

TikTok; Seattle (WA); In loco; USD 2.755.000 - 4.133.000; Part-time

Descrizione del lavoro

TikTok invites a motivated student to join our Global E-Commerce (TikTok Shop) team in Seattle as an intern. You will help build and rewrite an industrial recommendation system that serves a billion-scale user base across short-video, livestream, and product scenarios, covering retrieval, pre-ranking, ranking, and blending end to end.

This internship blends hands-on learning with professional development events and collaboration with industry experts, offering a unique opportunity to contribute

Mansioni

• Assist in building an industrial recommendation system for a billion-scale user base.
• Contribute to retrieval, pre-ranking, ranking, and blending components end-to-end.
• Collaborate with the Global E-Commerce Content Recommendation team on TikTok Shop.

Descrizione del lavoro

Location:

Seattle

Employment Type:

Intern

Job Code:

A22971A

Responsibilities

Global E-Commerce (TikTok Shop) is one of TikTok's fastest-growing businesses and a core driver of the company's revenue growth. Our Global E-Commerce Content Recommendation team owns the end-to-end recommendation stack for e-commerce video and image-text content on TikTok worldwide — retrieval, ranking, and multi-queue blending; supply ecosystem and cold start; and the browsing-to-purchase experience for hundreds of millions of users.We believe recommendation is being rewritten in the compute era. ID-based collaborative filtering and supervised learning built today's systems and still run most of the industry — but their returns are diminishing, and we are betting the next order of magnitude on rebuilding the stack on LLM foundations. Our ambition is to build the most advanced recommendation system in the world, and the next generation after that.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.You will help build — and rewrite — an industrial recommendation system serving a billion-scale user base across short-video, livestream, and product scenarios, covering retrieval, pre-ranking, ranking, and blending end to end