Principal Engineer, CUDA UMD - GPU Kernel Scheduling

NVIDIA is hiring a Principal Engineer, CUDA UMD - GPU Kernel Scheduling in Santa Clara, United States. It pays $272k-$431k a year and Level rates it ; you can apply on NVIDIA.

Level's read on this job

Builds AI ●●●● is how Level rates this role: the job is building AI systems.
Level classes it as a lead role.
NVIDIA has 2,800+ other open roles on Level.

AI in this role

NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. We're looking to grow our company, and form teams with the smartest people in the world. Join us at the forefront of technological advancement.

Are you a motivated system software engineer with a deep understanding of device drivers who has phenomenal C/C++ skills? If so, this role might be for you. We are looking for a seasoned software professional to work on the CUDA Driver, a core component of our platform for accelerating general purpose computation on the GPU. You will be an integral part of a team that delivers features and improvements to better realize the potential of NVIDIA hardware for a growing range of computational workloads, ranging from deep learning, scientific computation, data science and self-driving cars to video games and virtual reality.

What you'll be doing:
As a member of our team, you will use your design abilities, coding expertise, and creativity to deliver the best compute platform in the world. You will craft elegant solutions to exciting problems and shape the future direction of CUDA as you collaborate with your peers across NVIDIA.

Evangelize, architect, and implement new features
Coordinate and drive development efforts across multiple teams
Help define forward-looking improvements to the CUDA APIs and programming model
Extend important CUDA programming models and functionality such as CUDA Graphs
Explore ways to use Graphs to improve the scheduling of AI/ML workloads on our GPUS to be more efficient and faster.
Write effective, maintainable, and well-tested code
Develop code for multiple operating systems

What we need to see:

BS or MS degree in Computer Science, Electrical Engineering or related field (or equivalent experience)
Strong C and C++ programming skills
Minimum of 15+ years of related development experience (multiple positions for varying experience levels open)
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 as well as presentation skills

Ways to stand out from the crowd:

Prior experience with parallel computing - preferably writing CUDA Programs or Libraries that use CUDA
Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO
Knowledge of memory coherence and consistency models
Background with kernel mode development
Experience with Linux Systems Software development as well as experience maintaining and extending programming models or higher-level language support for similar environments

Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until November 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

How we rate this

Principal Engineer, CUDA UMD - GPU Kernel Scheduling at NVIDIA rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.