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

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul, and Tokyo.



Why Join Us

At TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.



Data-E-commerce-Global Supply Chain and Logistics team:

Our missions is to optimize the variety & cost-saving of goods and the speed & quality of fulfillment to ensure the user experience of global e-commerce service.



You'll work on:

- 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.



Role and Responsibilities:

- Responsible for the developing of deep learning models and related intelligent systems for the supply chain and logistics of international E-Commerce business.

- Participate in the process of optimizing the business results by using some of the following techniques: computer vision, natural language processing, sales prediction, time-series, geo-coding, etc..

- Keep track of cutting-edge technologies in the fields of computer vision, natural language processing and multi-modal machine learning; make use of these technologies to optimize the results in tasks such as fine-grained product style analysis, product similarity analysis and product attribute recognition, etc.