Senior Machine Learning Engineer, TikTok Live Stream

About the TeamRecommendation algorithm team plays a central role in the company, driving critical product decisions and platform growth.

The team is made up of machine learning researchers and engineers, who support and innovate on production recommendation models and drive product impact.

The team is dynamic, fast-pacing, collaborative and impact-driven.

Responsibilities - What You'II Do
- Take charge of certain directions in the recommendation algorithm of the live streaming business and make contributions to a world-class large scale recommendation system
- Take charge of optimizing the core algorithms and strategies (recall, coarse ranking, fine ranking, mixed ranking, diversity, through modeling technologies including deep learning, representation learning, multi-task learning, causal inference, and sequence modeling.

Ensure every user finds relevant creators and enjoys the fun of live streaming.
- Continuously improve recommendation technology with deep understanding of the ecological roles of users, creators, platforms, drive growth in user experience, creator growth, platform revenue, and create a virtuous cycle of livestream ecosystem
- Work closely with the product and operations team, excel in technological innovation with deep integration of business characteristics, and help achieve long-term and short-term business development goals.



Minimum Qualifications
- Has strong theoretical foundation and extensive practical experience in the field of machine learning/deep learning , familiar with at least one mainstream deep learning framework.
- Has exceptional ability to analyze and solve problems, passionate about solving challenging problems; good at communication, proactive at work, has a strong sense of responsibility, and possess good teamwork skills.
- Priority will be given to 1) individuals who have published papers at top conferences, won competitions such as ACM/machine learning, or have experience in core algorithm businesses such as large-scale recommendation systems, computational advertising, and search engines; or 2) individuals who have taken technical leadership or people management roles in the related fields