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# Senior Integration Engineer - Autonomous Vehicles

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $152,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** C++ (Programming Language), CMake, Nvidia CUDA, Computer Programming, Computer Engineering, Software Debugging, Linux, Distributed Systems, Game Engine, General-Purpose Computing on Graphics Processing Units, MISRA C (C Programming Language), Performance Tuning, Real-Time Operating Systems, Software Engineering, System Software, Systems Integration, Multithreading, Graphics Processing Unit (GPU), Git, Information Technology, Low Latency, Data Management, Software Version Control
- **Published:** May 19, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=3f7ba731fd187522

## About the Role

* PhD with 1+ year, MS with 3+ years, or BS (or equivalent experience) with 5+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
 * Excellent C and C++ programming skills.
 * Experience developing and debugging multithreaded/distributed applications like multimedia systems, game engines, etc. Profound knowledge of programming and debugging techniques.
 * Experience on developing software in heterogeneous architectures, including GPUs.
 * Background with version control systems GIT and build system like CMake/Bazel.
 * Be hands-on and work well within a team of algorithm, software and hardware engineers, with a significant level of detail orientation and a penchant for data organization and presentation.
 * Solid understanding of Linux, and/or other real-time operating systems.

Ways to stand out from the crowd:

 * Understanding of parallel, embedded and distributed architectures.
 * Great at writing low latency, highly performant code.
 * Great communication and analytical skills.
 * Self-motivated and a great teammate.

## Description

* Integrating modular software components (e.g. perception, planning, etc.) together to implement customer-required self-driving functions.
 * Optimizing product implementation to achieve target performance goals.
 * Diagnosing system software & functional driving issues reported on our target driving platforms, including on-road & simulation.
 * Create efficient mechanisms to improve utilization on computers with multiple heterogeneous hardware engines.
 * Performing in-vehicle tests, collecting data and completing autonomous drive missions.
 * Developing system tests, documentation of product functions, evaluating quality and proposing corrective actions.
 * Developing highly efficient product code in C++, making use of high algorithmic parallelism offered by GPGPU programming (CUDA).
 * Follow quality and safety standards such as defined by MISRA.


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