This role pays more than
98%
of similar roles. Most pay
$181,993–$256,000
— the shaded band above.
At the midpoint, this role pays about
$352k
versus about
$219k
for comparable roles.
Based on 240 similar postings.
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
892 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 870 roles with salary data.
Principal OEM Execution Lead, Autonomous Driving Solutions leads the end-to-end execution of NVIDIA DRIVE Autonomous Driving Software from product definition to production deployment across major vehicle lines. This role involves managing adaptation, integration, validation, and production readiness while coordinating between internal engineering teams and external automotive partners. You will translate vehicle requirements into technical commitments, build scalable workflows for various sensor configurations and compute platforms, and manage multi-functional implementation across functional safety, cybersecurity, and quality domains. The position requires expertise in system architecture, embedded systems, vehicle networks, and compliance standards such as ISO 26262 and ISO/SAE 21434. You will resolve complex technical issues, manage risk, and ensure product scalability. Key skills include experience with AUTOSAR, real-time operating systems, middleware, and SIL/HIL/VIL validation to industrialize autonomous driving software into safe, production-ready vehicles for the automotive industry.
Manage the end-to-end execution of autonomous driving software from initial product definition to production deployment across OEM vehicle lines.
Translate complex OEM vehicle requirements and use cases into clear technical commitments for internal engineering teams.
Develop scalable, repeatable workflows for adapting software to specific vehicle architectures, sensor configurations, and network systems.
Drive multi-functional implementation across functional safety, cybersecurity, platform software, and hardware integration.
Establish a rigorous operating cadence including risk management, decision logs, and objective readiness metrics for program milestones.
Resolve technical issues by determining root causes, clarifying ownership, and managing trade-offs across cross-functional teams.
Represent program health and technical readiness in high-level reviews with OEM leaders and internal executives.
Incorporate lessons learned from individual vehicle programs into product improvements, tooling, and documentation for future projects.
What we're looking for
BS or MS in Computer Science, Computer Engineering, Electrical Engineering, Robotics, or a related field, or equivalent experience.
15+ years of relevant experience in automotive software, autonomous driving, embedded systems, vehicle platforms, or other complex safety-critical domains.
Demonstrated success taking a complex automotive software product from requirements and architecture through integration, validation, SOP, and production support with a major OEM.
Strong technical understanding of system/software architecture, embedded compute, vehicle networks, sensor/actuator interfaces, diagnostics, and software release processes.
Working knowledge of automotive development and compliance practices including Automotive SPICE, ISO 26262, ISO/SAE 21434, SOTIF, and cybersecurity.
Proven ability to lead large multi-functional programs in a matrixed organization and resolve ambiguous issues across organizational boundaries.
Strong communication skills with the ability to balance OEM priorities, product integrity, safety, schedule, quality, and platform scalability.
Experience launching L2+/L3 autonomous driving or advanced driver-assistance functions on multiple vehicle lines (preferred).
Autonomous Vehicles
Machine Learning
ML ops
Data Ops
ADAS
L4 Robotaxi
Software Development
Product Roadmap
Validation
Data Collection
KPIs
Vehicle Systems