Drimva

TikTok

Machine Learning Engineer Graduate (Data-Global E-Commerce-Search) - 2027 Start (PhD)

Seattle, Washington · Full-time · Posted Oct 28, 2026

Education
Currently pursuing or recently completed a PhD in Computer Science, Electrical Engineering, Machine Learning, Artificial Intelligence, Information Retrieval, Natural Language Processing, Data Mining, Statistics, or a related technical field.
Visa sponsorship
Must establish authorization to work in the United States. The company does not provide sponsorship or any immigration-related benefits.

About the job

Conduct applied research and develop scalable machine-learning methods to improve TikTok’s global e-commerce search relevance, personalization, and user experience.

What you'll do

  • Research and improve search algorithms, including retrieval, ranking, relevance evaluation, and query understanding.
  • Apply NLP, computer vision, and LLMs to understand content and videos and match them to search queries.
  • Develop search personalization and translate research into scalable product improvements.

What they ask for

  • Currently pursuing or recently completed a PhD in a listed or related technical field.
  • Research or practical experience in at least one listed area, such as search, information retrieval, ranking, recommendation systems, NLP, multimodal learning, LLMs, data mining, or machine-learning systems.
  • Able to establish authorization to work in the United States; the company does not provide sponsorship or immigration-related benefits.
  • Able to commit to an onboarding date by the end of the year; state availability and graduation date in the resume.

Nice to have

  • Publications, preprints, patents, open-source contributions, or research projects in relevant areas.
  • Experience with large-scale retrieval, ranking, model training, evaluation, online experimentation, distributed systems, or production ML systems.

Tools

NLP, CV, LLM

AI focus

Apply machine learning, NLP, computer vision, and LLMs to search relevance, personalization, video understanding, retrieval, ranking, evaluation, and multimodal search.

Model-written summary · the original posting is authoritative

First seen Oct 28, 2026 · Last verified Nov 5, 2026 (UTC)