Senior Software Engineer, Longitudinal Planning – Autonomous Vehicles
Summary
Senior engineer on NVIDIA's China autonomous driving team who designs, tunes, and debugs longitudinal planning algorithms (speed generation, yield planning, trajectory planning) for production self-driving vehicles. Core work is C++/Python algorithm development, simulation and log analysis, and on-vehicle testing across L2–L4 programs.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world.
The NVIDIA China Autonomous Driving Team is looking for a hands-on senior software engineer to develop and improve longitudinal planning for production autonomous vehicles. You will work on key planning capabilities, including speed generation, speed adaptation, yield planning, and trajectory planning (TP). You will also perform deep issue analysis and support multiple production programs and vehicle platforms.
What you’ll be doing:
Design, develop, and optimize longitudinal planning algorithms for car following, stopping, yielding, merging, cut-in handling, intersections, and other complex driving scenarios
Develop and improve speed generation, speed adaptation, yield planning, and trajectory planning
Improve driving safety, comfort, efficiency, and robustness across different traffic conditions, road environments, and vehicle platforms
Adapt algorithms and tune parameters for different vehicle dynamics, powertrains, braking systems, actuator delays, and OEM requirements
Analyze, triage, and resolve complex Planning & Control issues across multiple autonomous driving programs from L2 through L4
Perform root-cause analysis using simulation, replay tools, vehicle logs, and on-vehicle diagnostics, and provide clear resolution proposals
Conduct on-vehicle testing and performance tuning to validate driving behavior in real-world scenarios
Collaborate with global teams and OEM partners on software integration, validation, and release readiness
Travel domestically and internationally for vehicle testing and customer collaboration as needed
What we need to see:
BS/MS in Computer Science, Electrical Engineering, Robotics, Vehicle Engineering, or a related field
3+ years of autonomous driving, ADAS, or robotics software development experience, with strong C++ and Python skills
Solid knowledge of speed planning, trajectory planning, vehicle dynamics, motion prediction, or numerical optimization
Experience with production software development, simulation, log analysis, on-vehicle debugging, and parameter tuning
Strong analytical, problem-solving, and English communication skills
Ways to stand out from the crowd:
Production experience developing longitudinal planning algorithms
Expertise in speed-profile optimization, space-time planning, model predictive control, or constrained numerical optimization
Experience handling interactive scenarios such as yielding, merging, cut-ins, intersections, and vulnerable road users
Knowledge of functional safety or autonomous driving validation standards
Familiarity with NVIDIA DriveOS, NVIDIA DRIVE AV, or direct OEM collaboration