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.