Senior Software Systems Engineer, L3 and L4 - Autonomous Driving

NVIDIA is an AI and computing technology company developing solutions for computers, robots, and autonomous vehicles. The Senior Software Systems Engineer will define requirements, analyze system performance, and establish testing and verification strategies for L3 and L4 autonomous driving products. The role also involves coordinating with engineering, safety, validation, data analytics, and product teams to advance safe and reliable autonomous driving systems.

Responsibilities:

• 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

Requirements:

• 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
• 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++