The Video-on-Demand (VoD) Algorithm team is responsible for optimizing the app experience related to performance for TikTok users. This team collaborates with all teams within and beyond the VoD team, to provide algorithmic support for end-to-end optimization solutions, including video shooting, uploading, processing, delivery, and playback, etc. 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. Responsibilities - Design and implement media streaming-related algorithms to improve TikTok user experience. Examples include video preloading, adaptive bitrate streaming (ABR), network bandwidth estimation, CDN traffic allocation, and transport-layer algorithms, to name a few. - Contribute to end-to-end media ecosystem design to improve the algorithmization of the multimedia system. - Run controlled experiments on millions of streaming sessions to validate improvements.

Minimum Qualifications - Bachelor's or Master’s degree in Computer Science, Computing Engineering, or related fields. - Industry or academic experience in the multimedia or network domain. - Proven ability to develop new algorithms and identify problems in existing solutions. - Fluent in statistics and data analysis. Preferred Qualifications - Experience with shipping software on behalf of a major brand at scale is a big plus. - Experience with learning-based model development is a big plus. 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