Principal Engineer, CUDA UMD - GPU Kernel Scheduling
$272k - $431k • US, CA, Santa Clara
Posted 1mo ago
Job Location
US, CA, Santa Clara
Tech Stack
Remote Work Policy
On-site
Categories
AI Infrastructure Engineer
About the job
NVIDIA is seeking a motivated system software engineer with deep understanding of device drivers and strong C/C++ skills to work on the CUDA Driver. This core platform component accelerates general-purpose computation on the GPU. You will be an integral part of a team delivering features and improvements to realize the full potential of NVIDIA hardware across diverse workloads, including deep learning, scientific computation, data science, self-driving cars, video games, and virtual reality. You will use your design abilities, coding expertise, and creativity to craft elegant solutions to exciting problems and shape the future direction of CUDA.
Responsibilities
- Architect and implement new features for the CUDA Driver.
- Coordinate and drive development efforts across multiple teams.
- Define forward-looking improvements to CUDA APIs and the programming model.
- Extend important CUDA programming models and functionality, such as CUDA Graphs.
- Explore using Graphs to improve the scheduling efficiency and speed of AI/ML workloads on GPUs.
- 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.
- 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 and presentation skills.
Benefits
- Equity
- Benefits