Senior Systems Software Engineer, CUDA Driver - Multi-Node and Memory Model

Nvidia

Confirmed live yesterday High trust

Remote

Quick summary

Work type: Remote
Location: Santa Clara, CAAustin, TX
Salary: $184,000–$287,500 / yr
Posted: 11 days ago
Freshness: Confirmed live yesterday
Closes: Nov 1, 2026
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $210k

This role $236k

$153k most similar roles pay here $302k

This role pays more than 79% of similar roles. Most pay $183,775–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $210k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Systems Software Engineer, CUDA Driver - Multi-Node and Memory Model

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Senior Systems Software Engineer, CUDA Driver - Multi-Node and Memory Model will join the team responsible for developing the CUDA Driver, a core component of the platform used to accelerate general purpose computation on the GPU. This role involves architecting and implementing new features related to memory models and multi-node scalability specifically geared toward next-generation AI applications. The engineer will coordinate development efforts across multiple teams, define improvements to CUDA APIs and programming models, and write maintainable code for various operating systems. Key requirements include expert C and C++ skills, experience with large codebases, and a deep understanding of memory coherency, consistency models, and system-level architecture like interconnects and virtual memory. The role addresses technical challenges in parallel computing to support workloads including deep learning, scientific computation, data science, and self-driving cars.

Skills

C C++ CUDA Parallel Computing Linux Windows Kernel Mode Development Virtual Memory System Software PyTorch Multi-node Scalability Operating System Interfaces

What you'll do

Develop and maintain the CUDA Driver to accelerate general purpose computation on GPUs.
Architect and implement new features for CUDA’s memory model and multi-node scalability.
Design and develop code for multiple operating systems in C and C++.
Define forward-looking improvements to CUDA APIs and programming models.
Coordinate and drive development efforts across multiple internal teams.
Write maintainable, well-tested code for high-performance computing workloads.
Solve complex problems related to memory coherency, consistency models, and system architecture.

What we're looking for

BS or MS degree in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
Strong C and C++ programming skills.
Minimum of 8 years of related development experience.
Experience driving projects across multiple teams.
Experience working with large codebases.
Background with operating system interfaces for threads, process control, and virtual memory.
Experience writing and debugging multithreaded programs.
Good written communication and presentation skills.

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