3 days ago
Base Salary
$184k - $288k/yr
Responsibilities
- Analyze application performance on NVIDIA GPUs using profiling tools.
- Identify and implement performance improvements in the MLIR/LLVM-based compiler middle end.
- Design and develop compiler passes and optimizations for robust, supportable compiler tools.
- Develop novel compilation-pipeline techniques for AI workload performance.
- Engage with the open-source LLVM community to improve integration.
- Collaborate with geographically distributed compiler, hardware, and application teams on improvements and problem resolution.
Requirements
- Bachelor’s, master’s, or Ph.D. in computer science, computer engineering, or a related field, or equivalent experience.
- 8+ years of experience in compiler optimizations, including loop, inter-procedural, and global optimizations.
- Excellent hands-on C++ programming skills.
- Understanding of at least one processor ISA; GPU ISA experience is a plus.
- Strong software engineering background focused on robust and maintainable solutions.
- Good communication and documentation skills and a self-motivated approach.
- Master’s or Ph.D. preferred.
- CUDA or other parallel programming experience, deep parallel programming knowledge, MLIR/LLVM/Clang compiler development experience, and familiarity with deep learning frameworks and NVIDIA GPUs are preferred.
Benefits
- Expected base salary range of 184,000 USD–287,500 USD.
- Eligible for equity and benefits.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.