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.
Engineering Lead - Applied Machine Learning
Didi autonomous driving is innovating the way we build our self-driving cars. We leverage our ride-sharing network to collect large amounts of data, and improve our algorithms with the data. In this role, you will lead a group of engineers to design, train and deploy ML models. It covers different algorithms across the whole stack. If you are interested in solving the exciting and challenging problems, and are enthusiastic about autonomous driving, please join us!
- Research, design, and develop new machine learning solutions and algorithms
- Drive high level algorithm decisions to ensure fast and accurate machine learning in a multitude of different applications
- Implement cutting edge machine learning techniques in object classification, labelling, pose estimation, and prediction
- Use real-time state estimation and context from surroundings to predict the motion of surrounding vehicles and pedestrians for use with vehicle path planning
- Work on data association, clustering, segmentation, filtering, and estimation
- Build robust, reliable systems to handle common and uncommon situations on the road
- PhD or MS in CS/CE/EE, or equivalent industry experience
- 5+ years of experience in related area
- Experience in leading an engineering team
- Extensive experience with ML frameworks such as Tensorflow, Caffe, and PyTorch
- Experience with machine learning and classification
- Strong programming skills in Python or C++
- Excellent mathematical reasoning skills, especially with probability
- Passionate about self driving car technology and its impact on the world
- Track record of driving ML research projects from start to completion, including conception, problem definition, experimentation, iteration, and finally publication or productization
- Experience with ROS, OpenCV, Gazebo, or PCL
- Experience with CUDA