As a Principal V&V Analytics Engineer on NVIDIA’s Autonomous Vehicles Verification and Validation team, you will lead the technical direction for evaluating and validating DRIVE AV software across various regions and vehicle platforms. Your day-to-day responsibilities include developing system architecture for data ingestion, metric calculation, behavioral assessment, and reporting, as well as establishing evaluation frameworks and guidelines that span multiple teams within the Automotive Business Unit. You will predict future validation platform needs, advise on technology investments, and mentor engineers to ensure high standards of code quality and system architecture. The role requires deep expertise in Python and C/C++, experience with cloud computing environments, and a background in autonomous vehicle validation or ADAS evaluation. Additionally, you should have strong leadership skills and the ability to communicate technical insights effectively across different levels within the organization.
Skills
Python
C++
Kubernetes
AWS
Docker
CI/CD
PostgreSQL
Prometheus
Grafana
GitLab
Jenkins
Ansible
Terraform
CUDA
Apache Spark
MESOS
ZooKeeper
Hadoop
TensorFlow
What you'll do
Develop comprehensive system architecture for AV evaluation and validation, covering data ingestion and reporting.
Establish technical standards and guidelines for evaluation frameworks and data pipelines across V&V organization.
Lead cross-team efforts to align evaluation infrastructure with requirements from various internal teams.
Predict future trends in validation platforms and advise leadership on technology investments.
Architect scalable cloud and GPU-accelerated compute strategies for large-scale metric evaluation.
Mentor engineers, set high standards for code quality, and guide complex architectural decisions.
What we're looking for
MS or PhD in Computer Science, Electrical Engineering, or related field with 15+ years of professional experience.
Proven ability to define system-level architecture for complex software platforms and mentor engineers.
Expertise in Python and C/C++ for developing production-quality libraries and APIs used by multiple teams.
Experience building and scaling data pipelines and evaluation infrastructure in cloud computing environments.
Strong leadership and communication skills, including presenting strategic recommendations to senior executives.
Deep background in autonomous vehicle validation or ADAS evaluation with experience defining safety metrics.
Demonstrated ability in developing GPU-accelerated or distributed computing pipelines for large datasets.
Market check
Salary context
This
$272,000–$431,250
range sits above
97%
of similar postings on FindRole.
Peer median band
$184,000–$260,000
Median floor and ceiling across peers.
Typical midpoint (25–75%)
$183,612–$250,700
Middle half of comparable postings.
Based on 240 comparable postings.*
* 240 is the maximum number of comparable postings sampled.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
802 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 798 roles with salary data.