Senior Machine Learning Engineer, Recommendation - TikTok eCommerce

• 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

• Bachelor or above degree in Computer Science or related fields with strong programming and problem-solving ability
• At least 3 years working experience in one of the following fields: recommendation algorithm, online advertising, information retrieval, natural language processing, computer vision, machine learning, large-scale data mining, or related fields

• Familiar with one or more of the algorithms such as Collaborative Filtering, Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks, Wide and Deep etc.
• Experience in Deep Learning Tools such as tensorflow/pytorch
• Experience with at least one programming language like C++/Python or equivalent

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.