Machine Learning Engineer - Fulfillment in London

At JD.com, also known as JINGDONG, we are building one of the world’s most trusted technology and supply chain ecosystems. What started as a bold idea in China has evolved into a NASDAQ-listed, Fortune 44 global enterprise serving over 700 million active customers. Powered by advanced logistics, innovative technology, and a commitment to integrity, JD.com operates across retail, logistics, technology, property and more, creating solutions that make everyday life smarter, faster, and more connected.

JD.com is expanding its international footprint through a digitally intelligent, cross-border supply chain and world-class logistics network, supported by platforms such as Joybuy, which brings trusted products to customers worldwide. Today, our teams operate across China, the U.S., U.K., Netherlands, France, Germany, Spain, Brazil, Hungary, Japan, South Korea, Australia, Thailand, Vietnam, Malaysia, Indonesia, Saudi Arabia, the UAE and beyond, reaching customers in every corner of the world.

Joining JD.com means becoming part of a company where people, innovation, and impact go hand in hand. We offer a competitive salary, a great location, and a supportive, people-first culture where your growth truly matters. With access to global projects, learning opportunities, and an inclusive environment that values every voice, you’ll have the space to shape the future with us.

You’ll be joining the JD.com team, which values collaboration, ownership, and a commitment to delivering high-quality results in a fast-paced, dynamic environment. We are building a next-generation inventory prediction & replenishment optimization platform to support JD’s global fulfilment services. We are looking for a Machine Learning Engineer who is passionate about turning machine learning and research into real, large-scale business impact.

As a Machine Learning Engineer focusing on demand forecasting, replenishment optimization, and supply chain decision intelligence, you will design, develop, and deploy models that support billions of worth of global inventory flow decisions. Your work directly influences forecast accuracy, stock availability, fulfilment cost, and customer experience.

• Design, implement, and evaluate machine learning models for demand forecasting, replenishment, and fulfilment optimization.
• Develop innovative algorithmic solutions to complex forecasting and supply chain problems in close collaboration with product, engineering, and operations teams.
• Contribute to the technical direction of the fulfilment intelligence platform and influence model architecture, system design, and best practices.
• Work onsite in London, UK.

• Bachelor’s degree in Engineering, Computer Science, Mathematics, or a related technical field.
• 3+ years of professional experience as a machine learning engineer or applied research scientist.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods and machine learning.
• Demonstrated ability to work independently with minimal guidance; proactively manage tasks and priorities across multiple projects; analyze and execute work efficiently; collaborate effectively with cross‑functional teams; and thrive in fast-paced, results-driven environments.
• Effective communication skills in English.

• Professional experience in e-commerce, retail forecasting, fulfilment logistics, inventory planning, or similar domains.
• Hands‑on experience with modeling tools such as Python, PyTorch, TensorFlow, scikit-learn etc.
• Hands‑on experience building large‑scale distributed machine learning systems such as Hadoop, Spark etc.
• Effective communication skills in Chinese.

At JD.com, we’re committed to building a diverse and inclusive workplace where everyone can thrive. We’re proud to be an equal opportunity employer and make all employment decisions without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, disability, age, veteran status, or any other protected characteristic.