Senior Software Engineer, Driving Behavior and Multi-Vehicle Adaptation – Autonomous Vehicles
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 software engineer to shape how vehicles plan, decide, and act on the road. In this role, you will own the driving behavior of our autonomous driving stack across multiple production programs — performing deep root-cause analysis, adapting planning and control algorithms to diverse vehicle platforms, and building automation tools that scale our engineering impact globally. You will ride in test vehicles, tune real-world performance, and collaborate directly with OEM partners to deliver safe, comfortable, and production-ready autonomous driving behavior.
What you’ll be doing:
Analyze, triage, and resolve complex Planning & Control (PnC) and Active Safety (AS) issues across multiple autonomous driving programs (L2, L2+, L2++, L3, L4)
Perform root-cause analysis on driving behavior bugs using replay tools and log-based diagnostics — covering path planning, lateral/longitudinal control, ALSA, AS, lane change, and emergency steering scenarios
Perform carline-specific adaptation and parameter tuning for PnC/AS modules across different vehicle platforms, ensuring driving behavior meets OEM requirements and regional regulations
Conduct on-vehicle testing, debugging, and performance tuning — ride along in test vehicles to validate planning and control behavior in real-world driving scenarios, diagnose on-site issues, and iterate on fixes
Communicate technical findings, bug analysis reports, and resolution proposals in English to global stakeholders, OEM partners, and cross-geo teams
Design and develop PnC testing tools, automated triage pipelines, and cross-carline comparison workflow — enabling systematic evaluation of behavior differences across vehicle platforms, accelerating bug classification, and reducing manual effort at scale
Support integration, validation, and release readiness activities for NDAS software releases
Travel domestically and internationally for on-site vehicle testing and customer collaboration as needed
What we need to see:
BS/MS in Computer Science, Electrical Engineering, Robotics, Vehicle Engineering, or related field
3+ years of experience in autonomous driving, ADAS, or robotics software development with strong C++ and Python skills
Solid understanding of motion planning, path planning, vehicle control, or active safety algorithms
Experience with on-vehicle debugging and real-time system diagnostics — CAN/Ethernet signal analysis, log-based replay, sensor validation, and parameter tuning on physical vehicles
Proficient English communication skills (written and verbal) — able to produce clear technical reports and participate in meetings with global teams
Ways to stand out from the crowd:
Multi-carline development experience — adapting and tuning PnC/AS parameters across different vehicle dynamics, steering systems, and brake characteristics
Experience building developer tools, test automation frameworks, or diagnostic platforms that improve engineering productivity
Familiarity with NVIDIA DriveOS / DRIVE AV platform and direct OEM customer collaboration
Knowledge of functional safety (ISO 26262) or ADAS testing standards (Euro NCAP, C-NCAP, GSR)
Willingness to travel and work on-site at test tracks or customer locations
Skills Required
- 3+ years of experience in autonomous driving, ADAS, or robotics software development
- Strong C++ and Python skills
- BS/MS in Computer Science, Electrical Engineering, Robotics, Vehicle Engineering, or related field
- Solid understanding of motion planning, path planning, vehicle control, or active safety algorithms
- Experience with on-vehicle debugging and real-time system diagnostics
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.
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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.
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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.
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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.”
