Engineer Graduate: (Machine Learning Engineer, Data-Search-Recommendation TikTok.US - Seattle) - 2026 Start (BS/MS)
Skip the busywork
ApplyBolt rewrites your resume for this exact role and hits submit. You just pick the jobs.
About this role
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 embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.
Responsibilities
We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok.
Successful candidates must be able to commit to an onboarding date by end of year 2026. 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.
Specific Responsibilities:
- Participate in the improvement of the search core algorithm, possible directions include:
- Content understanding/matching: Applying the industry's cutting-edge NLP and CV technology 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, and other technologies for better video understanding from the perspective of the video itself and social network, improve the authority, credibility, and usefulness of search results.