About the Company
DiDi's autonomous driving unit was established in 2016 with the mission of developing Level 4 autonomous driving (AD) technology to make transportation safer and more efficient. In August 2019, the unit became an independent company, DiDi Autonomous Driving, dedicated to advanced AD R&D, product application, and business expansion. We believe integrating AD technology into a shared-mobility fleet will generate immense social value. By leveraging DiDi's specialized technology, operational expertise, and integrated ecosystem, we are positioned to build and operate a highly efficient, user-oriented autonomous fleet.
About the Role
We are seeking a Staff or Senior Staff Software Engineer to lead the core path planning for our autonomous vehicles. You will architect high-performance systems for trajectory generation and optimization that form the foundation of our planning stack, while integrating ML model to further boost vehicle performance and behavior.
Responsibilities
- Architect the core path planning system for real-time trajectory generation and optimization, including geometric search, optimization, open space search etc.
- Lead performance optimization of motion planning algorithms and system architecture, leverage CPU/GPU to boost the computation efficiency.
- Drive the development of safety-critical, low-latency C++ modules.
- Provide technical leadership on software architecture and performance engineering.
- Manage the team by designing OKRs, setting milestones and performance review for the team members.
Qualifications
- M.S. or Ph.D. in CS, Robotics, or related field.
- 5+ years of experience in autonomous systems or robotics.
- Expert proficiency in C++ for safety-critical, real-time systems.
- Deep expertise in motion planning algorithms and system architecture.
- Proven track record as a technical lead shipping complex systems.
Preferred Qualifications
- Experience leading a planning or controls team in autonomous driving.
- Expertise in trajectory optimization and search-based planning.
- Background in system performance optimization for real-time system's efficiency.
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