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NVIDIA

engineering opportunity

Senior System Software Engineer - Autonomous Vehicles

The engineer will design and optimize software architecture for autonomous vehicle platforms, including sensor drivers, data streaming, and vehicle interface abstraction. They will also perform in-vehicle testing, develop unit tests, and ensure code quality according to safety standards like MISRA.

Santa Clara, California, United StatesonsiteFULL_TIME

Posted

About the role

What will you do at NVIDIA?

The Autonomous Vehicles Platform team is now looking for a Senior System Software Engineer. Our team builds the NVIDIA DriveWorks SDK with the goal to provide a scalable software stack and framework to build autonomous vehicles. We are seeking software engineers with interests in designing, developing and maintaining many aspects of the core technology around sensor drivers and interfaces, data streaming, data recording and playback, and vehicle interface abstraction.

What You Will Be Doing: Create and optimize software architecture and frameworks for real-world performance while matching or exceeding customer requirements. Working with vendors developing innovative sensors for vehicles. Developing sensor drivers, plug-ins, and processing functions around sensor data.

Create highly efficient sensor data recording, playback and visualization tools. Performing in-vehicle tests, collecting data and analyzing integrity. Working with our car teams and control teams to develop interfaces to the vehicles to enable self-driving.

Supporting data collection campaigns for our autonomous vehicle program. Developing unit tests, documentation for features, evaluating quality and proposing corrective actions. Creating highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA), and following quality and safety standards such as defined by MISRA.

What We Need to See: BS/MS in Computer Engineering, Computer Science or related field (or equivalent experience). Excellent C and C++ programming skills. 8+ years of proven experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc. Strong knowledge of programming and debugging techniques, especially for parallel and distributed architectures.

Background on Linux, Android, and/or other real-time operating systems. Experience with sensors such as cameras, LiDAR, radar, ultrasonics, IMU, GPS Experience with vehicle control interfaces. Thrive on writing low latency, highly performant code.

Great communication and analytical skills. Ways to Stand Out from the Crowd: Understanding of embedded architectures. Experience with data-parallel and/or GPGPU programming, CUDA, and OpenCL.

Software development for modern OpenGL (Core Profile) and Linux. Experience with version control systems GIT and build system CMake. 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 May 1, 2026.

This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse 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. NVIDIA pioneered accelerated computing. Today, our AI infrastructure powers global intelligence, transforming every industry.

Learn more about NVIDIA.

Which skills does this role require?

CC++Multithreaded programmingDistributed systemsCUDAGPGPUSensor driversLinuxReal-time operating systemsLiDARRadarCamera systemsEmbedded architecturesCMakeGitOpenGLAutonomous VehiclesDriveWorks SDKSensor DriversData StreamingMISRAEmbedded ArchitecturesAndroidRTOSUltrasonicsIMUGPSMultithreadingDistributed SystemsSoftware ArchitectureVehicle ControlUnit TestingData Parallelism

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