Join the NVIDIA's Solutions Engineering team that is reshaping the future of driving! Our goal is to build and deploy scalable solutions for autonomous vehicles and as a result, create safer and more efficient roads. Our team is hands-on, passionate about practical results, and values diversity.
You will help craft the application software architecture by working closely with external partners developing on our platform and on collaborations across multiple teams within NVIDIA working on autonomous vehicles. You will also advance and refine the overall drivability of our solution, focusing on integration challenges and using your deep analytical skills to tease through the complexity of the system to find effective solutions. NVIDIA is widely considered to be one of the technology world’s most desirable employers, and is committed to fostering a diverse work environment and proud to be an equal opportunity employer. If you are passionate in bringing autonomous vehicles into the world and see the solution come together, we would like to hear from you!
What you'll be doing:
Shape the application architecture internally, with a focus on perception & sensor fusion, by collaborating closely with architecture and software development teams.
Integrate and adapt NVIDIA solutions in target vehicles, ensuring that both perception and sensor fusion are adapted and tuned to meet the desired driving performance and functionality.
Lead bring-up activities and provide technical support to resolve functional and perception & sensor fusion related issues.
Perform and leverage in-vehicle and simulation test drives for functional and performance analysis on the recorded data.
Work with our partners to efficiently integrate hardware and software components, understand the system architecture, profile performance, identify bottlenecks, and drive optimization
Collaborate with our global engineering teams in our US, APAC, and Europe locations to deploy solutions to our customers.
What we need to see:
5+ years of work related experience in software development related to deep learning and/or autonomous driving technologies.
Experience developing and deploying deep learning-based perception solutions across diverse sensor modalities, including cameras, lidars, ultrasonics, and radar
Familiar with data flywheel for scaling deep learning-based perception solutions
Solid grasp on sensor processing pipelines and their lifecycle.
BS/MS in computer science, robotics, electrical engineering, or related technical field (or equivalent experience).
Excellent C/C++ development skills with good knowledge of Python.
Ability to adapt to fast paced development lifecycles and multi-functional organizations, new technologies and platforms.
Strong analytical skills, strive for innovative solutions, with outstanding attention to details.
Ways to stand out from the crowd:
Experience with automotive design processes and standards (e.g. ISO 26262 FuSa, ISO 21448 SOTIF, ASPICE), including in-vehicle testing, simulation and development guided by measurable outcomes.
Familiarity of NVIDIA DRIVE platform and NVIDIA GPU hardware and CUDA programming.
Software development experience on QNX or equivalent RTOS.
Contributions to or ownership of open-source project and mentorship experience.
You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.Skills Required
- 5+ years of related software development experience in deep learning and/or autonomous driving technologies
- Experience developing and deploying deep learning-based perception solutions across cameras, LiDAR, ultrasonic, and radar sensors
- Familiarity with the data flywheel for scaling deep learning-based perception solutions
- Strong understanding of sensor processing pipelines and their lifecycle
- Bachelor's or master's degree in computer science, robotics, electrical engineering, or a related technical field, or equivalent experience
- Excellent C/C++ development skills and good knowledge of Python
- Ability to work in fast-paced development lifecycles and multifunctional organizations
- Strong analytical skills, innovative problem-solving ability, and outstanding attention to detail
- Experience with automotive design processes and standards, including ISO 26262 FuSa, ISO 21448 SOTIF, or ASPICE
- Experience with in-vehicle testing, simulation, and development guided by measurable outcomes
- Familiarity with the NVIDIA DRIVE platform, NVIDIA GPU hardware, and CUDA programming
- Software development experience on QNX or an equivalent real-time operating system
- Contributions to or ownership of open-source projects and mentorship experience
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.”
