Senior Software Engineer

NVIDIA is seeking a Senior Software Engineer to join the Test Engineering team for NVIDIA Driver Assistance Systems (NDAS). You will help build and scale simulation and validation pipelines for advanced driver assistance systems. Your work will span data mining, automated labeling, benchmarking, CI/CD infrastructure, AI-assisted workflows, and large-scale test automation. Close collaboration with machine learning engineers, software developers, and systems engineers shapes the tools, datasets, metrics, and processes needed to evaluate complex autonomous driving systems.

Responsibilities:

• Design, curate, and maintain comprehensive test suites covering system requirements, edge cases, and failure modes across diverse road types, environmental conditions, and vehicle interactions.
• Architect and implement scalable evaluation tools and metrics that support critical system testing, verification, and release decisions.
• Build ground-truth datasets for ADAS features and develop LLM- and VLM-powered auto-labeling solutions that accelerate and scale data annotation workflows.
• Develop and improve simulation, replay testing, benchmarking, and CI/CD pipelines for efficient, repeatable, and large-scale validation.
• Create and refine standard operating procedures, labeling guidelines, and quality-control mechanisms, enabling established workflows to scale across internal and external labeling teams.
• Identify, reproduce, and debug system anomalies. Collaborate closely with cross-functional teams to determine root causes, drive timely resolution, and validate software fixes.
• Execute offline validation using internal test frameworks, analyze large and complex datasets, and produce reports with actionable insights that guide system improvements.
• Ensure validation activities follow applicable automotive safety standards, regulatory requirements, and industry best practices.

Requirements:

• Master's degree or Ph.D. in Computer Science, Electrical Engineering, Robotics, or a related technical field, or equivalent practical experience.
• 6+ years of hands-on experience in software development, testing, validation, or quality engineering, ideally in autonomous driving, automotive systems, robotics, or another safety-critical domain.
• Hands-on background in ADAS or autonomous driving systems, covering simulation, replay-based testing, and model-based development workflows.
• Strong programming and scripting skills in Python, C++, and Shell.
• Fluency with modern software testing practices, including unit, integration, system, and end-to-end testing.
• Experience designing or maintaining automated testing, benchmarking, or CI/CD infrastructure.
• Familiarity with modern AI technologies,including LLMs, VLMs, and AI agents,and a track record applying them to workflow automation, data labeling, or engineering productivity.
• Strong analytical, debugging, and problem-solving skills, with the ability to work effectively across multiple engineering disciplines.

Preferred Qualifications:

• A strong automation mindset and a track record of building software, platforms, or internal tools that significantly improve engineering efficiency and scalability.
• Hands-on work with data science methodologies, large-scale data analysis, and advanced SQL.
• Direct experience developing or validating production ADAS or autonomous driving features.
• Depth in LLM/VLM/agentic development frameworks.
• Exposure to distributed data-processing systems, large-scale simulation infrastructure, or agentic AI workflows.