
Engineer Graduate: (Machine Learning Engineer Graduate - Search E-Commerce - Seattle) - 2026 Start (PhD)
- Seattle, WA
- Permanent
- Full-time
- Improve the basic search quality and user experience: Optimize query analysis and text relevance matching.
- Understand e-commerce video content and implement multi-modal matching. Improve users' perception of product authority, and deeply participate in the design and implementation of core search products.
- Comprehensively improve the end-to-end shopping experience from browsing to after-sales.
- Design and implement the end-to-end ranking system (recall, first stage ranking, final stage ranking and mixed row): Improve users' personalized shopping interests model.
- Improve the shopping conversion efficiency for merchandise, video and live stream to promote GMV growth.
- Promote the robust development of the ecosystem: From the perspective of the industry and businesses, solve challenging problems such as supply and demand matching, business cold start, and sustainable business growth, etc.
- Think, analyze and adjust the evolution of the system to achieve long-term and sustainable growth of GMV.Qualifications:Minimum Qualifications:
- PhD in Computer Science, Machine Learning, Artificial Intelligence, Statistics, or a related field.
- Final year or recent graduate with a background in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
- Familiar with one or more of the following areas: recommendation systems, machine learning, deep learning, data mining, computer vision, NLP, or multimodal machine learning.
- Strong proficiency in Python and/or C/C++, and familiarity with a machine learning framework. Solid knowledge of data structure and algorithms.
- Excellent in analysis, modeling and problem-solving, and can see the essence of problems from complex data.
- Publication records in top journals or conferences will be a plus. Experience winning ACM-ICPC medals will be a plus.