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System Software Engineer – Nvsci
Company | NVIDIA |
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Location | Santa Clara, CA, USA |
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Salary | $148000 – $287500 |
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Type | Full-Time |
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Degrees | Bachelor’s, Master’s |
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Experience Level | Senior |
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Requirements
- BS, MS in CS/CE/EE or related engineering field or equivalent experience.
- 5+ 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.
Responsibilities
- Design 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 stakeholders to improve APIs, simplify system architecture, enhance software flexibility, maintainability and elevate developer experience.
- Evaluate trade-offs in resource-constrained environments and work closely with hardware and firmware engineers to optimize performance and maximize the potential of crucial middleware NvSci APIs.
- Lead end-to-end feature development for NvSci that meet 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.
Preferred Qualifications
- Knowledge of Automotive quality standards, ASPICE, ISO 26262, ISO 21434.
- Experience with formal verification methods and tools, such as Ada/SPARK and TLA+.
- Experience in process automation and workflow optimization in large-scale software environments.
- Understanding of the unique challenges in autonomous vehicle software systems, specifically safety, security, and real-time performance.