Architect and implement new features for the CUDA Driver to optimize GPU kernel scheduling and AI/ML workloads. Collaborate across teams to extend CUDA programming models and improve the overall compute platform.
Requirements
Requires a degree in Computer Science or Electrical Engineering with at least 4 years of experience in C/C++ and system-level software development. Candidates should have a strong understanding of OS interfaces, memory management, and multithreaded programming.
Key Skills
C, C++, CUDA, Device Drivers, Multithreading, Operating Systems, System Architecture, Kernel Mode Development, Parallel Computing, Linux Systems Software, Virtual Memory, Memory Hierarchy
Benefits
- Equity
Senior Software Engineer CUDA UMD - GPU Kernel Scheduling in santa clara at Unknown Company
This position is listed as full time and onsite.