Senior Data Scientist, Data Quality and AI Evaluation

At NVIDIA, we are building the next generation AI-native autonomous driving architecture — combining classical safety stacks, foundation models, and scalable AI systems into a unified production platform. Autonomous driving is entering a new era. Future AV systems will not be purely classical robotics stacks, nor purely end-to-end neural networks. The future lies in the deep integration of classical safety architectures and large-scale AI-driven systems. If you want to work on problems that build the future of autonomous systems over the next decade, this is the place.

What You’ll Be Doing

• Define quality metrics and evaluation methods that reveal where auto-labeling pipelines succeed, fail, or regress.
• Build and maintain human-verified golden datasets covering representative driving conditions, critical corner cases, historical failures, and new requirements.
• Analyze large-scale sensor, camera and annotation data to identify root causes, discover systematic errors, and prioritize improvements with perception and auto-labeling engineers.
• Develop automated approaches for failure clustering, similar-case discovery, and targeted selection of data for human correction.
• Build statistically sound audits and experiments, establish release acceptance criteria, and communicate findings through clear dashboards and recommendations.
• Partner with labeling operations to improve annotation guidelines, reviewer consistency, and the balance between quality, efficiency, and cost.

What We Need To See

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