Responsibilities
- 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.
Basic qualifications
- 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 Chinese and English.
Preferred qualifications
- 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.
Tags & focus areas
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