What you will be doing
Work with us to translate driving-feature needs and safety analysis into world-model requirements, performance targets and error budgets.
Investigate real-world failure modes and develop metrics, scenarios and tests that expose gaps across operating conditions.
Build and validate evaluators that connect world-model errors to vehicle behavior.
Partner with our data and ground-truth teams to define evaluation datasets and labeling guidelines, addressing ambiguous cases, label quality, coverage, provenance and independence from training data.
Develop reproducible analysis and automated triage using on-road data, replay and closed-loop simulation to distinguish product failures from evaluation and data issues.
Help us turn results into decisions through evaluation tools and dashboards that guide improvements and demonstrate release readiness.
What we need to see
MS or PhD in engineering, computer science, physics, data science or a related field, or equivalent experience.
8+ years of relevant experience in systems engineering, quantitative systems analysis, verification and validation, data science or experiment design for complex software systems.
Experience translating system needs and failure modes into measurable requirements, test strategies and acceptance criteria.
Experience evaluating perception, map-fusion or comparable systems, including evaluation-data strategies and ground-truth quality.
Strong Python and SQL skills, with experience building reproducible analyses and extracting insights from large datasets.
Experience building Python evaluation pipelines using distributed data-processing frameworks, object storage and SQL-based data platforms.
A foundation in statistical analysis, experiment design, measurement uncertainty and performance-budget allocation.
Attention to detail and ownership: you check assumptions, validate results and follow issues through to resolution.
Ability to build technical alignment across teams and communicate findings, limitations and trade-offs clearly.
Proficiency with SQL and Python or C++
Ways to stand out from the crowd
Experience evaluating perception, mapping or planning systems in autonomous vehicles, machine learning or computer vision contexts, with the ability to connect subsystem metrics to closed-loop vehicle behavior.
Strong data science and analytics background, with experience uncovering performance trends, failure patterns and coverage gaps across large datasets and building data-driven dashboards with web interfaces, backend APIs and evaluation visualizations.
Experience developing and validating evaluation tooling and reproducible workflows, including orchestration frameworks such as Temporal and validation methods for outputs from VLMs, LLMs or agentic triage pipelines.
Familiarity with automotive functional safety concepts, including fault-tree analysis and failure-rate allocation.
Software engineering proficiency in C++ and automated testing.
#AutonomousVehicles
- Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:
- 184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
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