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Engineer Graduate: (Machine Learning Engineer Graduate - Search E-Commerce - Seattle) - 2026 Start (PhD)
Engineer Graduate: (Machine Learning Engineer Graduate - Search E-Commerce - Seattle) - 2026 Start (PhD)TikTok • Seattle
Engineer Graduate : (Machine Learning Engineer Graduate - Search E-Commerce - Seattle) - 2026 Start (PhD)

Engineer Graduate : (Machine Learning Engineer Graduate - Search E-Commerce - Seattle) - 2026 Start (PhD)

TikTok • Seattle
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  • [job_card.full_time]
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Team Introduction

: The Search E-Commerce team spearheads the development of TikTok's advanced search algorithm, crucial for its booming global e-commerce platform. Utilizing state-of-the-art large-scale machine learning, along with cutting-edge NLP, CV, and multi-modal technologies, we are committed to creating a top-tier search engine. Our goal is to deliver the best e-commerce search experience to over a billion monthly TikTok users worldwide. Our mission is to create a world where "no reasonably priced product is difficult to sell." We are looking for talented individuals to join our team in 2025. 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. Applications will be reviewed on a rolling basis. We encourage you to apply early. Candidates can apply for a maximum of TWO positions and will be considered for jobs in the order you applied for. The application limit is applicable to TikTok and its affiliates globally. Responsibilities :

  • Improve the basic search quality and user experience : Optimize query analysis and text relevance matching. - Understand e-commerce video content and implement multi-modal matching. Improve users' perception of product authority, and deeply participate in the design and implementation of core search products.
  • Comprehensively improve the end-to-end shopping experience from browsing to after-sales.
  • Design and implement the end-to-end ranking system (recall, first stage ranking, final stage ranking and mixed row) : Improve users' personalized shopping interests model. - Improve the shopping conversion efficiency for merchandise, video and live stream to promote GMV growth.
  • Promote the robust development of the ecosystem : From the perspective of the industry and businesses, solve challenging problems such as supply and demand matching, business cold start, and sustainable business growth, etc.
  • Think, analyze and adjust the evolution of the system to achieve long-term and sustainable growth of GMV.

Minimum Qualifications :

  • PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
  • Final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
  • Familiar with one or more of the following areas : recommendation systems, machine learning, deep learning, data mining, computer vision, NLP, or multimodal machine learning.
  • Strong proficiency in Python and / or C / C++, and familiarity with a machine learning framework. Solid knowledge of data structure and algorithms.
  • Excellent in analysis, modeling and problem-solving, and can see the essence of problems from complex data.
  • Publication records in top journals or conferences will be a plus. Experience winning ACM-ICPC medals will be a plus.
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