Principal Engineer, CUDA UMD - Kernel Scheduling

Details

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 are looking to grow our company, and form teams with the smartest people in the world.

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.

Responsibilities

• Evangelize, architect, and implement new features for the CUDA Driver and related systems
• 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 GPUs to be more efficient and faster
• Write effective, maintainable, and well-tested code
• Develop code for multiple operating systems

Requirements

• 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

Preferred / Ways to stand out

• 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 I/O
• 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

Compensation & Benefits

• Base salary range: 272,000 USD - 431,250 USD (base salary will be determined based on location, experience, and pay of employees in similar positions)
• Eligible for equity and benefits (link to NVIDIA benefits)

Applications for this job will be accepted at least until March 19, 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 is an equal opportunity employer. We do not discriminate 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.