Senior Software Systems Engineer, L3 and L4 - Autonomous Driving

NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. They are seeking a Senior Software Systems Engineer to develop use cases and system requirements for autonomous driving products, perform system-level analysis, and drive innovation in systems engineering.

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++