Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the TikTok e-commerce community.
Explore and research cutting-edge technologies in machine learning/graph learning/sequence learning and related fields, implement these technologies in practical business scenarios, and support the production of scalable and optimised machine learning models.
Currently pursuing a PhD in Computer Science, engineering or quantitative field.
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Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience. Build logistics network knowledge graphs and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. Use NLP and LLM algorithms to handle address problems such as address verification and address suggestion.
Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc. We need strong machine learning and deep learning skills to detect important factors and model the relationship between the future and history.
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Participate in building a large-scale graph storage and graph learning platform to improve relationship building and governance within the TikTok e-commerce community.
Explore and research cutting-edge technologies in machine learning/graph learning/sequence learning and related fields, implement these technologies in practical business scenarios, and support the production of scalable and optimised machine learning models.
Final year PhD graduates in Computer Science, engineering or quantitative field.
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Responsible for the development of deep learning and operations research models and related intelligent systems for the supply chain and logistics of the global E-Commerce business.
Utilize e-commerce big data and deep learning models to predict end-to-end estimated time of arrival (ETA), and some logistics events such as failed delivery, delivered but not received to enhance the user logistics experience. Build logistics network knowledge graphs and predict the spatio-temporal trajectory sequence of express packages through deep learning, statistical inference and other algorithmic methods. Use NLP and LLM algorithms to handle address problems such as address verification and address suggestion.
Utilize time series forecasting techniques to predict sales at different granularities and horizons, such as warehouse-level manpower forecasting, inventory-level demand forecasting etc. We need strong machine learning and deep learning skills to detect important factors and model the relationship between the future and history.
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From our early days in a 750 sq ft warehouse with just 4 people, we’ve grown into one of Asia’s leading distributors for global beauty brands like Mustela, Embryolisse, Phyto, Dear Klairs, I'm From, Dr.Ceuracle, Wellage, Fation and Celimax.
And today, thousands of customers discover and purchase our products every day through Shopee, Lazada, and TikTok Shop.
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Position yourself for roles in e-commerce or digital marketing as you grow your portfolio of hosted sessions.
Want to turn product energy into genuine smiles and sales? Join our team working with us at AUSH MILBY GROUP SDN BHD, a retail brand bringing products to customers both in-store and online with a friendly, practical approach.
As a Live Host you will build engaging live shows and scale our online presence, creating honest product stories that convert viewers into returning customers.
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