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Senior Systems Software Engineer - Autonomous Vehicles

NVIDIA

Senior Systems Software Engineer - Autonomous Vehicles

full-timePosted: Aug 24, 2026Updated: Aug 27, 2026Santa Clara, CA, US

Job Description

Our ADAS Platform team is responsible for building a scalable and modular software stack that powers advanced driver-assistance systems across a diverse range of product lines and OEMs. We are looking for a highly motivated Senior Software Systems Engineer with a strong foundation in software architecture. This role is ideal for someone who thrives on working across multiple layers of the software stack to drive modularization, improve abstraction, and enable extensibility and reuse. You will play a key role in evolving the platform to support efficient integration and scalability in a complex multi-OEM environment.What you will be doing:Driving architectural improvements that simplify and modularize the software stack.Designing clean boundaries between NVIDIA core components and OEM-specific implementations.Refactoring ADAS components to support reuse, extensibility, and long-term maintainability.Improving system-level scalability through IPC, middleware, and platform abstraction layers.Partnering with teams across software, systems, and hardware to define clear interfaces and improve integration velocity.Establishing test coverage, design reviews, and architectural documentation that scales with the platform.Profiling and tuning system performance — optimizing for modern multi-core and real-time environments.What we need to see:BS or MS in Computer Engineering, Computer Science, or a related field (or equivalent experience).8+ years of professional software development experience.Solid background in C and C++ programming.Strong understanding of modular software architecture, clean code design, and separation of concerns.Hands-on experience building and debugging multithreaded, real-time, or performance-critical systems.Familiarity with parallel/distributed systems and low-level system profiling.Comfortable working in Linux, QNX, or other embedded RTOS environments.Exceptional communication skills and a collaborative, hard-working attitude.Ways to Stand Out From The Crowd:Experience developing ADAS software.Deep understanding of real-time operating systems, particularly QNX.Familiarity with the automotive software lifecycle and integration across safety-critical systems.Experience using Git and Bazel in large-scale software environments.Ability to work across system, hardware, and algorithm teams with precision and clarity.Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 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 August 28, 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.

Locations

  • Santa Clara, CA, US

Responsibilities

  • Driving architectural improvements that simplify and modularize the software stack.
  • Designing clean boundaries between NVIDIA core components and OEM-specific implementations.
  • Refactoring ADAS components to support reuse, extensibility, and long-term maintainability.
  • Improving system-level scalability through IPC, middleware, and platform abstraction layers.
  • Partnering with teams across software, systems, and hardware to define clear interfaces and improve integration velocity.
  • Establishing test coverage, design reviews, and architectural documentation that scales with the platform.
  • Profiling and tuning system performance — optimizing for modern multi-core and real-time environments.
  • Driving architectural improvements that simplify and modularize the software stack.
  • Designing clean boundaries between NVIDIA core components and OEM-specific implementations.
  • Refactoring ADAS components to support reuse, extensibility, and long-term maintainability.
  • Improving system-level scalability through IPC, middleware, and platform abstraction layers.
  • Partnering with teams across software, systems, and hardware to define clear interfaces and improve integration velocity.
  • Establishing test coverage, design reviews, and architectural documentation that scales with the platform.
  • Profiling and tuning system performance — optimizing for modern multi-core and real-time environments.
  • This posting is for an existing vacancy.
  • NVIDIA uses AI tools in its recruiting processes.

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