Tiktok - San Jose, CA
posted 3 days ago
TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. The E-commerce Global Supply Chain and Logistics team is dedicated to enhancing clients' shopping experience and reducing logistics operational costs in TikTok E-commerce. We are currently seeking talented software engineers with 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. As a Machine Learning Engineer, you will be responsible for building deep learning and statistical models to provide end-to-end estimated time of arrival (ETA) predictions for e-commerce logistics. You will fine-tune ETA expressions to improve the click-to-order rate while balancing negative review indicators. Additionally, you will utilize data mining tools to construct logistics network knowledge graphs, which will enable the development of a situational awareness and early warning system for logistics fulfillment. This system will help operations discover and address logistics network anomalies, ultimately improving fulfillment quality in collaboration with logistics service providers. Your role will also involve analyzing and predicting the spatio-temporal trajectory sequences of express packages using deep learning, statistical inference, and other algorithmic methods. This trajectory prediction will enhance our understanding of logistics network dynamics, improve ETA prediction accuracy, and provide essential sample features for other prediction tasks. Furthermore, you will build a service network design (SND) model for selecting locations for transshipment centers and last-mile stations based on expected increases in logistics order volume. By deeply understanding supply chain and logistics scenarios, you will extract directions for optimizing logistics operations, reducing costs, and improving service quality. Finally, you will develop innovative and state-of-the-art e-commerce logistics models and algorithms.