Senior Machine Learning Engineer - TikTok E-commerce Global Supply Chain and Logistics

The E-commerce Global Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing logistics operational cost in TikTok E-commerce. We are currently looking for talented software engineers that have a deep understanding of machine learning (ML), operations research (OR), data mining and statistical inference. This position can be fulfilled in our San Jose and Seattle offices.

Responsibilities - Build deep learning and statistical models to provide end-to-end estimated time of arrival (ETA) prediction for the e-commerce logistics. Through fine adjustment of ETA expression to the consumers, improve the click-to-order rate while balancing the negative review indicators. - Use data mining tools to build logistics network knowledge graphs, based on which to construct a situational awareness & early warning system for logistics fulfillment, enabling operations to discover and deal with logistics network anomalies, and to improve the logistics fulfillment quality together with logistics service providers. - Analyze and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. This trajectory prediction can help to build a better understanding of logistics network dynamics, improve ETA prediction accuracy and provide important sample features for other prediction tasks. - Build a service network design (SND) model for the location selection of transshipment centers and last mile stations based on an expected increase in logistics order volume. - Extract the direction of logistics operation optimization, cost reduction and service quality improvement by in-depth understanding of supply chain and logistics scenarios. - Develop innovative and state-of-the-art e-commerce logistics models and algorithms

Minimum Qualifications - Master's or PhD degree in Computer Science, Engineering, Operations Research or related fields. - Strong in data structures and algorithms, with excellent problem-solving ability and programming skills - Experience in applied machine learning, familiar with one or more algorithms such as Matrix Factorization, Factorization Machines, Word2vec, Logistic Regression, Gradient Boosting Trees, Deep Neural Networks etc. - Experience with at least one of the Big Data tools (For eg. Hive sql/Spark/Mapreduce; at least one of the Deep Learning tools(For eg. Tensorflow/Pytorch).

Preferred Qualifications - Work experience in e-commerce, supply chain, logistics, transportation or related fields is preferred. - Publications at KDD、NeurIPS、WWW、SIGIR、WSDM、CIKM、ICLR、ICML、IJCAI、AAAI and related conferences. - 3+ years of working experience in machine learning, operations research or big data analysis.