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.

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