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

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. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

This full-time Graduate role provides early-career engineers the opportunity to join one of our engineering teams where you will have the opportunity to: Participate in the improvement of the search core algorithm, possible directions include: - Content understanding: Applying the industry's cutting-edge NLP and CV technology and leveraging LLM to match the most relevant videos for each search query, and continuously improve the relevance of TikTok search. - User Behavior Modeling: solving the recommendation problem in search, let TikTok search increase the ability of personalization on the basis of "relevant", and understand users better. - Video understanding: comprehensive use of NLP, CV, as well as LLM for better video understanding from the perspective of the video itself and social network, improve authority, credibility, and usefulness of search results. - Search systems engineering: designing, building, testing, and maintaining search services, data pipelines, tools, or platform components that support search quality, reliability, latency, and user experience.