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Validation Data Scientist, Verification and Validation - Autonomous Vehicles

NVIDIA

3 Locations permanent

Posted: March 16, 2026

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Quick Summary

An NVIDIA engineer will work closely with cross-functional teams to validate and verify autonomous vehicle data, ensuring high-quality output and meeting the performance requirements of our AI platform.

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 Scientist 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 lead 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.

• Build 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.

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

• Working closely with our Software Product, Testing and Development teams, you will turn open-ended safety and performance questions into clear quantitative analyses that influence what we build next.

• Develop dashboards, reports, and documentation 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 science, data engineering, or analytics roles working with large‑scale data, ideally in safety-critical domains.

• 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 senior leaders.

• Ability to compose clear user documentation, technical guides, and executive‑level summaries.

Ways To Stand Out From The Crowd:

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

• Proven track record architecting 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 leading technical direction for a data or analytics team, including setting standards for code quality, metrics, and validation methodologies.

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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