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# System Software Engineer

- **Company:** NVIDIA Ltd.
- **Location:** Santa Clara, CA, United States
- **Experience:** Expert
- **Salary:** $184,000.0 - $287,500.0
- **Contract:** Permanent contract
- **Skills:** Application Programming Interfaces (APIs), C++ (Programming Language), Microprocessors, Middleware, Firmware, ISO/IEC 15504, Software Engineering, Systems Architecture, Reliability of Systems, Generative AI, Hardware Acceleration
- **Published:** July 22, 2026
- **Apply:** https://www.dice.com/job-detail/b46f4857-d04d-4ceb-876b-ebd692cee966

## About the Role

* BS, MS in CS/CE/EE or related engineering field or equivalent experience.
 * 8+ years of relevant software development experience.
 * Proficiency in C/C++.
 * Experience in system architecture, embedded systems, building complex systems with multiple threads, CPUs, accelerators, and chips.
 * Strong understanding of Operating Systems.
 * Excellent written and verbal communication skills, ability to clearly convey complex technical concepts.
 * Problem-solving skills, with a track record of driving solutions from concept to production.
 * Ability to work effectively in cross-functional, distributed teams.

## Description

* Build and implement next-generation NvSci software to enable seamless cross-platform functionality and efficient integration with user applications, hardware acceleration libraries, and frameworks on various SoCs.
 * Collaborate with internal and external collaborators to improve APIs, simplify system architecture, enhance software flexibility and maintainability, and elevate developer experience.
 * Evaluate trade-offs in resource-constrained environments and work closely with hardware and firmware engineers to optimize performance and improve the potential of crucial middleware NvSci APIs.
 * Lead end-to-end feature development for NvSci that meets stringent automotive safety and security standards (ISO 26262, ASPICE, ISO 21434), aligning with product roadmaps and release cycles.
 * Research and integrate sophisticated software engineering practices, automation tools, and generative AI technologies to improve software reliability, maintainability, and scalability.


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