Senior Software Test Engineer, L3 and L4 - Autonomous Driving

Overview

NVIDIA is pursuing the potential of AI to define the next era of computing, with GPUs serving as the intelligence behind computing, robotics, and autonomous vehicles. This role focuses on test strategy and validation for L3/L4 autonomous driving products, collaborating with engineering, safety, and product teams to drive testing and comprehension of product progress.

What You’ll Be Doing

• Develop test strategy and use cases/scenarios for L3 and L4 autonomous driving products based on customer needs, traffic regulations, certification standards, and industry guidelines.
• Define test strategy and execution plan on vehicle platform.
• Formulate test cases and define critical performance metrics to ensure compliance with functional and safety requirements.
• Collaborate with stakeholders to define KPIs and evaluate product progress by analyzing test data and results.
• Establish strong multi-functional relationships with collaborators across engineering, safety, and product teams.
• Scale and innovate the product operational design domain (ODD) by designing campaigns and roadmaps.
• Lead L3/L4 vehicle integration and retrofitting, managing end-to-end processes to advance testing and validation schedules.
• Spearhead data triage and root cause analysis, driving issue resolution and generating comprehensive test reports.
• Promote and cultivate a strong systems engineering approach across the organization.

What We Need To See

• MS or PhD in Engineering, Physics, Computer Science, or a related field (or equivalent experience).
• 10+ years proven experience in ADAS, system analysis, data analysis, and software architecture.
• 3+ years of experience driving the mass-production launch of autonomous driving products, including supervised FSD, urban NOA, or equivalent features.
• Proficiency in programming languages commonly used in AV development and testing (e.g., Python, C++) and familiarity with data query and analysis tools.
• Awareness of functional safety (ISO 26262), Safety of the Intended Functionality (SOTIF / ISO 21448), and V-model validation methodologies.
• 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.
• Deep understanding of autonomous vehicle sensor suites (LiDAR, Radar, Camera, Ultrasonic) and their specific failure modes, edge cases, and validation requirements.
• Provide technical mentorship to junior engineers and lead by example in establishing rigorous testing and validation standards.

Ways To Stand Out From The Crowd

• Experience contributing to a launched L3/L4 autonomous vehicle program.
• Hands-on experience with testing strategy for ADAS, large-scale datasets, data analytics workflows.
• Innovation by tools/out of the box thinking to resolve the problem statement.
• Passionate and self-motivated about autonomous technology.