The Machine Learning infra team builds and supports the essential tools, frameworks and pipelines for every machine learning engineer at Didi autonomous driving. Our goal is to fully utilize the enormous quantity of the daily collected sensor and driver behavior data, greatly accelerate the development cycle of machine learning models across the whole company, empowering machine learning engineers to focus on improving the car’s safety and performance, instead of worrying about their infrastructure. Our scope covers the whole lifecycle of machine learning: intelligent data collection, data mining and data annotation, model training, model evaluation and debugging, model optimization and deployment to vehicles. We care about performance, ease of use and reliability of our products.

Responsibilities:

  • Design, implement and deploy offboardinfra and tools to support machine learning models training/optimization/deployment and data collection/mining/annotation workflows.
  • Own technical projects from start to finish and be responsible for major technical decisions and tradeoffs. Effectively participate in team’s planning, code reviews and design discussions.
  • Consider the effects of projects across multiple teams and proactively manage conflicts. Work closely with partner teams to ensure they are benefiting from the systems we built.

Qualifications:

  • Strong coding in Python and experience with C++.
  • Must have the experience in at least one of the following:
    • Data mining (e.g. active learning) for autonomous driving
    • Automatic data annotation
  • Passionate about self-driving technology and its potential impact on the world
  • BS, MS or PhD in CS, Math or equivalent real-world experience

Preferred:

  • Experience with deep learning frameworks like PyTorch, TensorFlow, etc.
  • Experience with MLOps platforms such as Kubeflow etc.
  • Understanding of distributed ML model training, model deployment (e.g., TensorRT conversion)
  • Experience building software solutions on cloud infrastructure
  • Experience working with Docker and Kubernetes
  • Knowledge and experience with machine learning algorithms
  • 3+ years of experience in the industry

 

 

 

About the Company:

Didi Chuxing (“DiDi”) is the world’s leading mobile transportation platform. We’re committed to working with communities and partners to solve the world’s transportation, environmental, and employment challenges by using big data-driven deep-learning algorithms that optimize resource allocation.

Didi Chuxing’s Autonomous-Driving team was established in 2016, and has grown to a comprehensive research and development organization covering HD mapping, perception, behavior prediction, planning and control, infrastructure and simulation, labeling, hardware, mechanical, problem diagnosis, vehicle modifications, connected car, and security, among others. We’re developing and testing self-driving vehicles in China and the United States.

In August 2019, DiDi upgraded its autonomous driving unit to an independent company to focus on R&D, product application, and business development related to self-driving technologies. The new company will integrate the resources and technology of DiDi’s platform, continue to increase investment in R&D, and deepen collaboration with auto industry partners.

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