Machine Learning Engineer - Feed E-Commerce - Singapore

About the Team:

We Are the 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 our 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 our platform.
• Build industry leading recommendation system; develop highly scalable classifiers and tools leveraging machine learning

Requirements:

Minimum Qualifications:

1. Bachelor's degree in computer science or a related technical discipline, with at least 2 years of related work experience;
2. Solid experience with data structures and algorithms;
3. Software development experience through hands on coding in a general purpose programming language;
4. Experience in one or more of the following areas: machine learning, recommendation systems, data mining or other related areas;
5. Strong communication and teamwork skills;
6. Passion about technologies and solving challenging problems.

Preferred Qualifications:

1. More than 3 years experience in the recommendation algorithm domain.