Forecasting & Replenishment ML Engineer (Global Supply Chain)

Jingdong Development France; Greater London; On-site; GBP 120,000 - 150,000; Full time

Job summary

JD.com in London is seeking a Machine Learning Engineer to design, develop, and deploy forecasting and replenishment models for a global fulfilment platform. You'll turn research into large-scale business impact, collaborating with product, engineering, and operations teams.

You will work on demand forecasting, inventory optimization, and supply chain decision intelligence, shaping model architectures and achieving improvements in forecast accuracy, stock availability, and customer experience.

Qualifications

• Bachelor's degree inEngineering, Computer Science, Mathematics, or related field.
• 3+ years of experience as a ML engineer or applied researcher.
• Experience programming in Java, C++, Python or related language.
• Experience with neural deep learning methods.
• Effective communication skills in English.

Responsibilities

• Design, implement, and evaluate ML models for demand forecasting, replenishment, and fulfilment optimization.
• Collaborate with product, engineering, and operations teams to deliver scalable forecasting solutions.
• Contribute to the technical direction of the fulfilment intelligence platform and influence model architecture and system design.
• Work onsite in London, UK.

Skills

English communication

Analytical thinking

Cross-functional collaboration

Independent work in fast-paced env

Education

Bachelor's degree in Engineering/CS/Math

Tools

Java

C++

Python

PyTorch

TensorFlow

scikit-learn

Hadoop

Spark

Job description

JD.com in London is seeking a Machine Learning Engineer to design, develop, and deploy forecasting and replenishment models for a global fulfilment platform. You'll turn research into large-scale business impact, collaborating with product, engineering, and operations teams.

You will work on demand forecasting, inventory optimization, and supply chain decision intelligence, shaping model architectures and achieving improvements in forecast accuracy, stock availability, and customer experience.