Engineer Graduate: (Machine Learning Engineer Graduate-Data-Search-TikTok) - 2026 Start (BS/MS)

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About the team On the TikTok Search Team, you will have the opportunity to develop and apply cutting edge machine learning technologies in real-time large-scale systems, which serve billions of search requests every day. Via advanced NLP and multi-modal models, our projects impact and improve the search experience for hundreds of millions of users globally. We are also exploring how to leverage LLM to further enhance TikTok users search experience, potentially sharping the search engine for the next generation. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving. Responsibilities: 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.
Minimum Qualifications: - Final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline. - Must obtain work authorization in country of employment at the time of hire, and maintain ongoing work authorization during employment. - Proficient coding skills and strong algorithm & data structure basis. - Effective communication and teamwork skills. - Experience in one or more of the following areas: NLP, Ranking, Ads, search engine, recommender system, distributed system, and machine learning. Privacy Statement By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https:///legal/privacy
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Location:
San Jose

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