Machine Learning Engineer - Feed E-Commerce - Singapore
Singapore, Singapore
Team Intro
We Are the TikTok ROW E-commerce Short Video&Live Recommendation Team. As pioneers reshaping global shopping experiences, we specialize in end-to-end optimization of short video recommendation systems across Europe, Southeast Asia, and Latin America. Our mission spans the full recommendation pipeline - from content supply, candidate retrieval, pre-ranking, ranking, blending to user experience refinement - building a culture-adaptive recommendation engine for TikTok's diverse markets.
Breaking through traditional "product shelf" e-commerce paradigms, we reinvent recommendation systems for the short video era. Our team combines academic excellence from top global universities with industrial expertise in billion-DAU recommendation systems. By leveraging cutting-edge machine learning technologies, we create dynamic intelligent matching bridges between massive product catalogs and global users.
We are committed to providing a personalized, proactive, and efficient consumption experience for users through live-stream e-commerce content by connecting them with exceptional sellers and high-quality products.
Our team is responsible for developing innovative recommendation algorithms and techniques to enhance user engagement and satisfaction, effectively transforming creative ideas into business-impacting solutions.
Responsibilities:
- Design and apply machine learning algorithm and recommendation strategies to improve users' experience on e-commerce content, including videos and livestreams.
- Understand ecosystem of e-commerce content and use algorithm and strategy to make it thrive.
- Work with product and ops team to deliver features that drives growth of e-commerce content on TikTok.
- Build industry leading recommendation system; develop highly scalable classifiers and tools leveraging machine learning
We Are the TikTok ROW E-commerce Short Video&Live Recommendation Team. As pioneers reshaping global shopping experiences, we specialize in end-to-end optimization of short video recommendation systems across Europe, Southeast Asia, and Latin America. Our mission spans the full recommendation pipeline - from content supply, candidate retrieval, pre-ranking, ranking, blending to user experience refinement - building a culture-adaptive recommendation engine for TikTok's diverse markets.
Breaking through traditional "product shelf" e-commerce paradigms, we reinvent recommendation systems for the short video era. Our team combines academic excellence from top global universities with industrial expertise in billion-DAU recommendation systems. By leveraging cutting-edge machine learning technologies, we create dynamic intelligent matching bridges between massive product catalogs and global users.
We are committed to providing a personalized, proactive, and efficient consumption experience for users through live-stream e-commerce content by connecting them with exceptional sellers and high-quality products.
Our team is responsible for developing innovative recommendation algorithms and techniques to enhance user engagement and satisfaction, effectively transforming creative ideas into business-impacting solutions.
Responsibilities:
- Design and apply machine learning algorithm and recommendation strategies to improve users' experience on e-commerce content, including videos and livestreams.
- Understand ecosystem of e-commerce content and use algorithm and strategy to make it thrive.
- Work with product and ops team to deliver features that drives growth of e-commerce content on TikTok.
- Build industry leading recommendation system; develop highly scalable classifiers and tools leveraging machine learning
* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰
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Categories:
Engineering Jobs
Machine Learning Jobs
Tags: E-commerce Industrial Machine Learning
Perks/benefits: Career development
Region:
Asia/Pacific
Country:
Singapore
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