NVIDIA Logo

NVIDIA

Senior Software Engineer CUDA UMD - GPU Kernel Scheduling

Posted 15 Days Ago
Be an Early Applicant
In-Office
Santa Clara, CA, USA
152K-288K Annually
Senior level
In-Office
Santa Clara, CA, USA
152K-288K Annually
Senior level
Design, implement, and improve NVIDIA’s CUDA Driver and programming models, including CUDA Graphs and GPU kernel scheduling for AI/ML workloads. Lead cross-team development, define CUDA API improvements, develop well-tested code across operating systems, and address system-level challenges involving operating systems, memory, threads, and GPU architecture.
The summary above was generated by AI

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 4 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

  • Understanding of system level architecture, such as interconnects, memory hierarchy, interrupts, and memory-mapped IO

  • 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

  • Knowledge of memory coherence and consistency models

  • Background with kernel mode development

  • Experience with Linux Systems Software development

  • 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 5, 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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

Similar Jobs

33 Minutes Ago
Hybrid
San Francisco, CA, USA
200K-275K Annually
Expert/Leader
200K-275K Annually
Expert/Leader
Artificial Intelligence • Enterprise Web • Sales • Software
Own Attio’s startup ecosystem strategy in the Bay Area, driving adoption among YC, accelerator, Series A, and leading VC portfolio companies. Build strategic partnerships with investors and ecosystem leaders, create founder-focused events and content, develop trusted relationships, and coordinate with product, sales, and marketing to remove adoption barriers. The role requires founder-level autonomy, strong startup ecosystem credibility, exceptional communication, and a track record of delivering impactful programs.
Top Skills: CRM
An Hour Ago
Remote or Hybrid
2 Locations
164K-297K Annually
Expert/Leader
164K-297K Annually
Expert/Leader
Fintech • Payments • Software • Financial Services
Lead commercialization of emerging AI products by securing enterprise customers and strategic partners, structuring pilots, and converting them into scaled relationships. Own engagements from prospecting and negotiation through launch and optimization, while partnering with Product and Engineering to shape product strategy, pricing, implementation, and go-to-market models.
Top Skills: AICloud InfrastructureData InfrastructureDeveloper Platforms
An Hour Ago
Remote or Hybrid
2 Locations
240K-359K Annually
Expert/Leader
240K-359K Annually
Expert/Leader
Fintech • Payments • Software • Financial Services
Own commercialization of Block’s emerging AI products from early pilots through scaled enterprise adoption. Develop market strategy, positioning, pricing, partnerships, and routes to market; personally secure lighthouse enterprise customers and strategic partners; design pilots that convert to production relationships; establish repeatable GTM, sales, implementation, and expansion processes; and build the commercial organization as product-market fit develops. Partner closely with Product and Engineering while shaping an emerging AI business.
Top Skills: AICloud InfrastructureData InfrastructureDeveloper Platforms

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account