Role OverviewThe Machine Learning Engineer Graduate will join the Global E-commerce Recommendation Live Algorithm team, responsible for the core recommendation stack for live commerce. The team operates in a highly dynamic environment where live room status changes in real time, conversion signals are sparse, and user intent must be understood across content, commerce, and transaction scenarios.
What You Will Do
As a Machine Learning Engineer Graduate, you will build and optimize recommendation models across recall, pre-ranking, ranking, and mixed ranking to improve GMV, conversion, watch time, and long-term user value. You will develop cross-domain and multimodal modeling solutions that connect videos, live streams, products, and user behavior to better power live commerce recommendations.
Why It Might Be a Fit
Successful candidates must be able to commit to an onboarding date by the end of the year. The team is looking for talented individuals who can pursue bold ideas, tackle complex challenges, and unlock limitless growth.
Requirements
- Individuals who are completing or have recently completed a Bachelor’s degree in Computer Science, Electrical Engineering, Mathematics, Statistics or a related discipline.
- Solid foundation in machine learning and at least one of the following areas: recommendation systems, search, advertising, NLP, multimodal learning, or large-scale applied AI.
- Strong programming skills in Python or C++, and hands-on experience with deep learning frameworks such as PyTorch.
- Good understanding of data structures, algorithms, and large-scale model training or production machine learning systems.
- Strong analytical and problem-solving skills, with the ability to translate business problems into effective modeling solutions.
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