About the Team: The Data-Search-TikTok-Local Services team enhances local services by improving user discovery of hospitality, dining, and leisure experiences while driving ecosystem growth. They leverage large-scale machine learning to refine search and recommendation systems, focusing on personalized relevance, CTR/CVR prediction, and optimized conversion efficiency for billions of users.
Responsibilities:
- Support the local video service business to enhance user discovery of life services such as hospitality, dining, and leisure.
- Improve the search experience in local services and promote ecosystem growth.
- Utilize large-scale machine learning techniques in search and recommendation scenarios with billions of users to: Improve user shopping experiences & Enhance conversion efficiency.
- Design and implement local services search algorithms across the full stack, including: Query analysis, relevance, recall, coarse ranking, fine ranking, and blended ranking. Personalized behavior modeling for relevance computation. CTR (Click-Through Rate) prediction, CVR (Conversion Rate) prediction. Vector recall and value blending.
Requirements
Minimum Qualifications
- Excellent analytical and problem-solving skills.
- Strong foundation in machine learning and deep learning, with experience in: NLP (Natural Language Processing).
- Exceptional coding skills with solid knowledge of data structures and algorithms.
- Proficiency in Linux development environments.
Preferred Qualifications
- Prior experience in search, recommendation, or advertisement algorithms.
- Familiarity with local life services and e-commerce businesses.