Principal Engineer, CUDA UMD - GPU Kernel Scheduling

Reposted 11 Days Ago
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Santa Clara, CA, USA
In-Office
272K-431K Annually
Expert/Leader
Artificial Intelligence • Computer Vision • Hardware • Robotics • Metaverse
The Role
As a Principal Engineer, you will enhance the CUDA Driver and collaborate with teams to improve GPU capabilities for various computational tasks, focusing on AI and deep learning workloads.
Summary Generated by Built In

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 the pay of employees in similar positions. The base salary range 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 April 14, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.

Skills Required

  • 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
  • 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

NVIDIA Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.

  • Equity Value & Accessibility Equity awards and a discounted ESPP are highlighted as core parts of total compensation, enabling employees to share in the company’s success. Stock-based compensation and the two-year lookback ESPP are consistently described as especially valuable.
  • Healthcare Strength Health coverage is portrayed as robust, with comprehensive medical, dental, and vision options alongside mental health support and on-site care resources. Employer HSA contributions and wellness perks reinforce the depth of the offering.
  • Retirement Support Retirement programs are depicted as strong, featuring a meaningful 401(k) match with Roth options and support for Mega Backdoor Roth contributions. These elements position long-term savings as a notable advantage of the total rewards package.

NVIDIA Insights

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The Company
HQ: Santa Clara, CA
21,960 Employees
Year Founded: 1993

What We Do

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. Today, NVIDIA is increasingly known as “the AI computing company.”

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