About the job
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 research scientists that focus on E-commerce recommendations. We are responsible for building up and scaling our recommendation system to provide the most stable and best shopping experience for our TikTok users.
Responsibilities
Responsible for the build and design of optimization algorithm strategies for large-scale (10 million to 100 million products or creators' contents) e-commerce recommendation algorithm pipeline
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.
Qualifications
Minimum
Bachelor above degree in computer science or relevant areas.
3+ years of experience with a solid foundation in data structure and algorithm design, and be proficient in using one of the programming languages such as Python, Java, C++, R, etc.;
Familiar with common machine/deep learning, causal inference, and operational optimization algorithms, including classification, regression, clustering methods, as well as mathematical programming and heuristic algorithms;
Familiar with at least one framework of TensorFlow / PyTorch / MXNet and its training and deployment details,as well as the training acceleration methods such as mixed precision training and distributed training;
Familiar with big data related frameworks and application, those who are familiar with MR or Spark are preferred
Preferred
Experience in recommendation systems, online advertising, ranking, search, information retrieval, natural language processing, machine learning, large-scale data mining, or related fields.
Publications at KDD, NeurlPS, WWW, SIGIR, WSDM, ICML, IJCAI, AAAI, RECSYS and related conferences/journals, or experience in data mining/machine learning competitions such as Kaggle/KDD-cup etc.