Applied Scientist- TikTok E-Commerce Recommendation

E-commerce is a new and fast growing business that aims at connecting all customers to excellent sellers and quality products on TikTok Shop, through E-commerce live-streaming, E-commerce short videos, and commodity recommendation. We are a group of applied machine learning engineers and data scientists that focus on E-commerce recommendations. We are developing innovative algorithms and techniques to improve user engagement and satisfaction, converting creative ideas into business-impacting solutions. We are interested and excited in applying large scale machine learning to solve various real-world problems in E-commerce.Responsibilities:• Participate in building large-scale (10 million to 100 million) e-commerce recommendation algorithms and systems, including commodity recommendations, live stream recommendations, short video recommendations etc in TikTok.• Build long and short term user interest models, analyze and extract relevant information from large amounts of various data and design algorithms to explore users' latent interests efficiently.• Design, develop, evaluate and iterate on predictive models for candidate generation and ranking(eg. Click Through Rate and Conversion Rate prediction) , including, but not limited to building real-time data pipelines, feature engineering, model optimization and innovation.• Design and build supporting/debugging tools as needed.Minimum Qualifications:• MS/PhD in Computer Science, related technical field or equivalent industrial research experience.• 3+ years of working experience in one of the following fields: recommendation algorithm, online advertising, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.Preferred Qualifications:• Familiar with at least one of the mainstream deep learning frameworks, like TensorFlow or PyTorch.• Passionate about solving complex and challenging problemsReq ID: A88143