Senior Software Systems Engineer, L3 and L4 - Autonomous Driving

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++.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 5, 2026.

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.