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JD.com in London, UK is seeking a Machine Learning Engineer focused on demand forecasting, replenishment optimisation, and supply chain decision intelligence to design, develop, and deploy models impacting billions of dollars’ worth of global inventory decisions.
The role emphasizes collaboration with product, engineering, and operations teams, high-impact experimentation, and building scalable systems in a fast-paced retail tech environment.
JD.com (NASDAQ: JD and HKEX: 9618), also known as JINGDONG, has evolved from a pioneering e-commerce platform into a leading technology and service provider with supply chain at its core. Renowned for its supply chain innovation and excellence, the company has expanded into sectors including retail, technology, logistics, healthcare, and more, aiming to transform traditional business models with cutting-edge digital solutions. Know more about us: https://corporate.jd.com/
We are looking for a Machine Learning Engineer who is passionate about turning machine learning and research into real, large-scale business impact to build a next-generation inventory prediction & replenishment optimisation platform at Joybuy (https://www.joybuy.com/). Joybuy is JD.com’s European full-category online retail brand designed to bring customers a faster, more convenient, and cost-effective shopping experience. Offering same-day and next-day delivery across the UK, Joybuy combines speed, reliability, and affordability to meet the needs of modern shoppers. As a Machine Learning Engineer focusing on demand forecasting, replenishment optimisation, and supply chain decision intelligence, you will design, develop, and deploy models that support billions of dollars ' worth of global inventory flow decisions. Your work directly influences forecast accuracy, stock availability, fulfilment cost, and customer experience.
JD.com is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.