Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU serves as the intelligence behind computers, robots, and autonomous vehicles that perceive the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. We pioneered a supercharged form of computing loved by the most demanding computer users in the world - scientists, designers, artists, and gamers. It’s not just technology though! It is our people, some of the brightest in the world, and our diverse company culture make NVIDIA one of the most fun, innovative and dynamic places to work in the world! At the center of NVIDIA's culture are our core values like innovation, excellence and determination and team, that guide us to be the best we can be. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is motivated to perform at their highest level. Come join the team and see how we can make a lasting impact on the world.
What you’ll be doing:
Develop use cases and system requirements for L3 and L4 autonomous driving products based on customer needs, traffic regulations, certification standards, and industry guidelines.
Perform system-level analysis to define performance requirements and allocate performance budgets across subsystems.
Formulate test cases and define critical performance metrics to ensure compliance with functional and safety requirements.
Define and drive online and offline test strategy and execution at both vehicle and component levels.
Partner closely with Data Analytics, Test Engineering, and System Integration & Test teams. Ensure the right evaluators and important metrics are developed. Prove that datasets cover sufficient scenarios and requirements. Target appropriate sampling strategies through Data Collection and Real-World Driving.
Establish strong multi-functional relationships with collaborators across engineering, safety, validation, and product teams.
Drive innovation in requirements decomposition, traceability, and verification processes.
Promote and cultivate a strong systems engineering approach across the organization.
What we need to see:
To succeed in this role, you should have:
MS or PhD in Engineering, Physics, Computer Science, or a related field (or equivalent experience).
8+ years proven experience in safety-critical systems engineering, system analysis, data analysis, and software architecture.
Strong software development background with proven coding skills.
Hands-on experience in SOTIF analysis (ISO 21448), functional safety (ISO 26262), and multi-functional architectural trade-off analysis.
Strong leadership and interpersonal skills, with the ability to drive alignment across large organizations.
Proven understanding of trade-offs between End-to-End deep learning approaches, classical modular perception/planning stacks, and associated validation and test strategies.
Ways to Stand Out from the crowd:
Experience contributing to a launched L3/L4 autonomous vehicle program.
Experience in AI safety and safety validation for ML-based systems.
Hands-on experience with large-scale datasets, data science, and analytics workflows.
Strong software engineering experience with proficiency in Python, SQL, and C++.
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 a diverse 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
- MS or PhD in Engineering, Physics, Computer Science, or related field
- 8+ years proven experience in safety-critical systems engineering
- Strong software development background with proven coding skills
- Hands-on experience in SOTIF analysis and functional safety
- Strong leadership and interpersonal skills
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.”
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