Senior Software Engineer | Enterprise | Full-Stack
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Design and optimize lateral planning algorithms for production autonomous vehicles, including lane keeping, lane changes, merging, and obstacle avoidance. This senior role requires 3+ years of autonomous driving or robotics software development experience, with strong C++ and Python skills and solid knowledge of path planning and vehicle kinematics. You'll analyze complex issues across multiple programs, conduct on-vehicle testing, and collaborate with global teams. Based in China with domestic and international travel required.
Written from this posting by Neural Jobs AI. The full description is below.
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 lateral planning for production autonomous vehicles. You will work on key planning capabilities, including SILC decision, driving rail generation and selection, path decision and nudge behavior, and path planning and optimization. You will also perform deep issue analysis and support multiple production programs and vehicle platforms.
What you’ll be doing:
Design, develop, and optimize lateral planning algorithms for lane keeping, lane changes, merging, obstacle avoidance, road-edge handling, and other complex driving scenarios
Develop and improve SILC decision, driving rail generation and selection, path decision and nudge behavior, and path planning and optimization
Improve path safety, feasibility, smoothness, and robustness across different road geometries, traffic conditions, and vehicle platforms
Adapt algorithms and tune parameters for different vehicle dynamics, steering systems, sensor configurations, 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 path planning, behavior planning, vehicle kinematics, collision checking, 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 lateral planning algorithms
Expertise in path optimization, search-based planning, obstacle nudging, or driving rail selection
Experience handling complex scenarios such as lane changes, merging, obstacle avoidance, and road-edge interactions
Knowledge of functional safety or autonomous driving validation standards
Familiarity with NVIDIA DriveOS, NVIDIA DRIVE AV, or direct OEM collaboration
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NVIDIA builds the GPUs and the CUDA software stack that most modern AI is trained and served on, along with its own research in graphics, robotics and foundation models.
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