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Validation Data Engineer, Verification and Validation - Autonomous Vehicles

NVIDIA

China, Shanghai permanent

Posted: March 16, 2026

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Quick Summary

As a Validation Data Engineer, Verification and Validation for autonomous vehicles, you will be responsible for ensuring the accuracy and reliability of data, working closely with cross-functional teams to identify and resolve data quality issues, and collaborating with subject matter experts to develop and implement data validation workflows.

Job Description

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.

The Autonomous Vehicles Verification and Validation (AV V&V) team is hiring a Validation Data Engineer to build tooling, perform large‑scale analysis, and drive data‑driven evaluation of vehicle‑level behavior and Operational Design Domain (ODD) coverage during scaled testing. We are a core part of how NVIDIA scales and validates DRIVE AV software across regions, customers, and vehicle platforms, and we're looking for someone who is excited to help shape the future of safe autonomous driving!

What You’ll Be Doing:

• In this role, you will work on large‑scale driving behavior and ODD analysis using extensive real-world and virtual AV driving logs to evaluate safety, comfort, and overall vehicle-level performance.

• Implement and improve evaluation frameworks, data pipelines, and data curation strategies to support robust analysis across thousands of test miles every single day.

• Define and compute core metrics that quantify AV performance against target ODDs, powering our product development flywheel, technical reviews, and AV software releases.

• Contribute to scalable workflows that use cloud platforms, modern data engineering tools, and AI workflows to surface insights, spot regressions, and enable data‑driven decision making.

• Work closely with our Software Product, Testing and Development teams to turn open-ended safety and performance questions into clear quantitative analyses.

• Develop dashboards and reports that make sophisticated validation results easy to understand and act on for both engineering and senior leadership.

What We Need To See:

• MS or PhD in Computer Science, Mathematics, Statistics, Electrical/Computer Engineering, or a related quantitative field, or equivalent experience.

• 5+ years of proven experience in data engineering or analytics roles working with large‑scale data; data science experience is a plus.

• Experience analyzing behavior of autonomous vehicles, ADAS systems, or other safety‑critical cyber‑physical systems.

• Strong Python skills, including writing production‑quality code and libraries for data processing, analysis, and automation.

• Hands‑on experience building and operating data pipelines in a production environment with cloud computing platforms.

• Excellent communication and teamwork skills, with a track record of working across teams and presenting your findings to technical collaborators.

• Ability to create clear dashboards, visualizations, and concise summaries for different audiences.

Ways To Stand Out From The Crowd:

• Background in statistics including experimental design, hypothesis testing, confidence intervals, and explaining results for non‑experts.

• Experience designing and scaling data and ML/AI pipelines to process and analyze very large telemetry or log datasets.

• Experience with GPU‑accelerated and/or distributed computing for large‑scale data processing and model evaluation.

• Familiarity with simulation‑based validation, vehicle‑level testing, and interpreting fleet test or on‑road validation data.

• Experience contributing to technical direction for a data or analytics team, such as helping define metrics, validation methods, or coding guidelines.

If you enjoy asking questions like “How do we know it’s safe enough?” and “What does the data really say?”, you’ll feel right at home here, and we’d love to hear from you! Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com/

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