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
Skills Required
- Bachelor’s or master’s degree in Computer Science, Electrical Engineering, Robotics, Vehicle Engineering, or a related field
- 3+ years of autonomous driving, ADAS, or robotics software development experience
- Strong C++ and Python programming skills
- 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
- Production experience developing longitudinal planning algorithms
- Expertise in speed-profile optimization, space-time planning, model predictive control, or constrained numerical optimization
- Experience with 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
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
-
Healthcare Strength — Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
-
Retirement Support — Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.
NVIDIA Insights
What We Do
NVIDIA’s 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. Today, NVIDIA is increasingly known as “the AI computing company.”
