Senior Systems Software Engineer - Autonomous Vehicles

NVIDIA•Us, CA

17h•$184,000 - $356,500

About The Position

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.

Requirements

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.

Nice To Haves

Experience developing ADAS software — especially in components like Planning, Sensor Fusion, Mapping, or Localization.
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.

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.