About the job
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 global logistic and warehousing network, improve operations efficiency and reduce operational cost with data analysis, machine learning and opeartion research methods.
Create supply chain's data portrait and knowledge graph in various dimensions such as vendors, commodity, place of origin, inventory, production capacity and quality of fulfillment, etc. Establish data-driven control-adjustment methods that enhance operational outcomes and user experience.
Highlight global e-commerce trends to optimize e-commerce commodity supplies, forecast commodity demand, recommend vendor stocking and enhance production capacity.
Responsible for designing optimization algorithm strategies for order allocation systems, able to meet diverse goals and constraints.
Responsible for estimating the probability of core decision variables in the order allocation system and building simulation capabilities, continuously improving estimation accuracy.
Responsible for the design of optimization algorithm strategies for commodity/freight pricing in multiple modes for domestic/cross-border scenarios, collaborating with upstream and downstream partners to optimize subsidy pricing and achieve the best price.
Responsible for modeling the probability estimation problems of logistics costs/benefits, price elasticity, etc., and continuously improving accuracy through machine learning and causal inference methods.
Deeply understand the e-commerce business scenario, and refine the direction of logistics operation mode optimization, logistics cost reduction, and service quality improvement through data mining;
Participate in product design, work closely with product, operations, and management teams to promote the productization and implementation of algorithm models to continuously empower business.
Qualifications
Minimum
Have 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;
Preferred
Have strong practical ability, winners in Kaggle, COCO, ImageNet, NOI/IOI and other competitions are preferred, and those who have papers published in relevant competitions and top academic conferences (such as CVPR, ICCV, ECCV, ACL, EMNLP, etc.) are preferred as well;
Familiar with big data related frameworks and application, those who are familiar with MR or Spark are preferred