1 day ago
Shanghai, China or Beijing, ChinaSenior
Responsibilities
- Own end-to-end Planning and Control integration across the autonomous driving software stack, including module interfaces, data flow, timing, and cross-team integration and validation.
- Design, develop, optimize, and integrate planning and control algorithms for L2, L2+, and L2++ driving scenarios.
- Adapt and tune planning and control modules across vehicle platforms with differing vehicle dynamics, steering systems, braking characteristics, sensor configurations, and OEM requirements.
- Build and maintain cross-carline integration validation workflows and comparison tools.
- Improve the safety, comfort, feasibility, smoothness, and system-level robustness of integrated planning and control systems.
- Analyze, triage, and resolve cross-module integration and functional issues across autonomous driving programs from L2 through L4.
- Perform root-cause analysis, bring-up validation, performance tuning, simulation, replay analysis, log analysis, on-vehicle diagnostics, and real-world testing.
- Collaborate with global teams and OEM partners on integration, validation, release readiness, and production delivery.
Requirements
- BS or MS in Computer Science, Electrical Engineering, Robotics, Vehicle Engineering, or a related field.
- At least 5 years of autonomous driving, ADAS, or robotics software development experience.
- Strong C++ and Python skills.
- Knowledge of motion planning, trajectory planning, vehicle control, vehicle dynamics, vehicle kinematics, or numerical optimization.
- Hands-on experience integrating planning and control modules into a production or prototype autonomous driving software stack.
- Experience with multi-carline adaptation, on-vehicle debugging, parameter tuning, simulation, log analysis, and production software development.
- Strong analytical, problem-solving, and English communication skills.
- Preferred experience developing and integrating autonomous driving or ADAS planning and control algorithms in production.
- Preferred experience with path and speed planning, trajectory optimization, model predictive control, constrained numerical optimization, functional safety, autonomous driving validation standards, developer tools, test automation frameworks, or cross-carline comparison workflows.
Benefits
- Domestic and international travel for on-vehicle integration testing and customer collaboration may be required.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.