Job Description
About the teamWe are a group of applied machine learning engineers and data scientists that focus on general feed recommendations and 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.What you will do:• Participate in building large-scale (10 million to 100 million) 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.In order to enhance collaboration and cross-functional partnerships, among other things, at this time, our organization follows a hybrid work schedule that requires employees to work in the office 3 days a week, or as directed by their manager/department. We regularly review our hybrid work model, and the specific requirements may change at any time.
TikTok is a short-video-sharing app and social network platform. The company's mission is to capture and present the world's creativity, knowledge, and precious life moments, directly from the mobile phone. TikTok enables everyone to be a creator and encourages users to share their passion and creative expression through their videos.
