Senior Software Engineer, CUDA UMD - Graphs and GPU Sharing

Nvidia

Quick summary

Work type: On-site
Location: Santa Clara, CA
Salary: $184,000–$287,500 / yr
Posted: 4 days ago
Closes: Sep 15, 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

$148k most similar roles pay here $302k

This role pays more than 81% of similar roles. Most pay $184,975–$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 942 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 931 roles with salary data.

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At a glance

TL;DR · Senior Software Engineer, CUDA UMD - Graphs and GPU Sharing

Role Posting Log in to save

Join our team as a seasoned system software engineer to work on the CUDA Driver, a critical component of NVIDIA’s platform for accelerating general computation on GPUs. You will collaborate closely with peers to deliver innovative features and improvements, enhancing the potential of NVIDIA hardware across diverse computational tasks including deep learning, scientific computing, data science, self-driving cars, video games, and virtual reality. Your responsibilities include evangelizing new ideas, architecting solutions, implementing features like CUDA Graphs and MPS, and coordinating development efforts across multiple teams. Ideal candidates possess strong C/C++ programming skills, a background in computer science or electrical engineering, at least 8-10 years of relevant experience, and expertise in Linux systems software development along with parallel computing knowledge, particularly in CUDA.

Skills

C C++ CUDA Linux GPU Parallel Computing Device Drivers

What you'll do

Develop new features and extend existing CUDA programming models.
Coordinate development efforts across various internal teams.
Implement enhancements to CUDA Graphs and MPS functionality.
Craft efficient solutions for complex problems in GPU computing.
Shape the future direction of CUDA through innovative contributions.

What we're looking for

BS or MS in Computer Science, Electrical Engineering or equivalent experience.
8-10 years of related software development experience.
Proficient in C and C++ programming languages.
Experience driving projects across multiple teams.
Strong knowledge of parallel computing, preferably with CUDA.
Expertise in Linux systems software development.

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