Research Scientist Graduate (Global E-commerce Content Recommendation) - 2026 Start (PhD)

Team Introduction Global E-Commerce Content Recommendation team plays a central role in the company, driving critical product decisions and platform growth. The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact. The team is fast-pacing, collaborative and impact-driven.

In today’s content-driven commerce landscape, traditional collaborative filtering and supervised learning methods are no longer sufficient. We’re actively exploring how large language models (LLMs) and generative AI can fundamentally transform the recommendation process: from retrieval to ranking, and from static listings to dynamic, generative user-item interactions.

We are looking for talented individuals to join our team in 2026. As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities. Co-create a future driven by your inspiration with TikTok.

Successful candidates must be able to commit to an onboarding date by end of year 2026

We will prioritize candidates who are able to commit to these start dates. Please state your availability and graduation date clearly in your resume.

Applications will be reviewed on a rolling basis. We encourage you to apply early.

Responsibilities

• Design algorithms and systems that leverage LLMs and generative models for content-to-commerce matching, product summarization, etc - Explore novel architectures and strategies for generative recommendation systems - Contribute to the research community via internal papers, patents, or external publications - Drive scientific rigor while balancing real-world constraints