Machine Learning Engineer
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.
- Build efficient and scalable data and machine learning pipeline to support DiDi’s fast global expansion.
- Implement and productionize machine learning models and optimization algorithms designed by data scientists.
- Machine learning: If you have related experience or strong interest, you will also have a lot of opportunities to directly build machine learning models.
- BS/MS degree in Computer Science or a related technical field, or equivalent practical experience.
- 2+ years of industry experience in software development.
- Experience with building big data pipelines.
- Experience 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.
- Experience with Flink and/or Spark streaming.
- Experience as a machine learning engineer before, closely working with data scientists/researchers.
- Experience working in a product and/or business-driven environment.
- Experience with building backend services.
- Have data science skills and experience with building machine learning models.
- Knowledge of deep learning and experience with a DL framework (e.g., TensorFlow, PyTorch).
- Experience with recommendation systems, information retrieval and personalization.
Note: Some international travel might be needed (preferred, not required).
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