Team Introduction

The International Business Technology Team is responsible for expanding DiDi’s global footprint and establishing DiDi’s global presence. This effort will leverage existing application and service infrastructure to build DiDi’s overseas products. Our team will be the vanguard of DiDi’s international expansion initiative. Here you will work to elevate the experiences of our global customers, improve DiDi’s operational and marketplace efficiency and build the products that will continue to change the global transportation landscape.


  • Participate in design, architecture, implementation, and support of machine learning systems behind the related products, including pricing, incentives, recommendation systems, ranking, etc.
  • Implement and productionize machine learning models and optimization algorithms designed by data scientists. 


  • 3+ years of industry experience as a software engineer. 
  • BS/MS degree in Computer Science or a related technical field, or equivalent practical experience.
  • Experience with building scalable machine learning systems. Note: the candidate needs to have experience with building backend services as well, to be able to take care of the online model serving part.
  • Experience with building big data pipelines. Familiar with Spark and Hive.
  • Proficiency in Python is a must. Experience with data science/machine learning related libraries (e.g., pandas, numpy, scikit-learn).
  • Basic knowledge of classical machine learning algorithms.
  • Strong verbal and written communication skills.
  • Can work in a fast-paced environment.

Bonus Points

  • Experience with Flink and/or Spark streaming.
  • Experience with building deep learning systems and familiar with a DL framework (e.g., TensorFlow, PyTorch).
  • Experience working in a product and/or business-driven environment.
  • Engineering experience with recommendation systems and ranking.
  • Engineering experience with online learning and/or reinforcement learning.

Note: Some international travel might be needed (preferred, not required).

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