1 day 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 optimizer.
- Develop novel compilation-pipeline ideas for AI workloads.
- Design and develop robust compiler passes and optimizations.
- Engage with the open-source LLVM community to improve integration.
- Collaborate with 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 a processor ISA; GPU ISA knowledge is a plus.
- Strong software engineering background focused on robust and maintainable solutions.
- Good communication and documentation skills and self-motivation.
- Master’s or Ph.D. preferred.
- Experience developing applications in CUDA or another parallel programming language preferred.
- Deep understanding of parallel programming concepts preferred.
- MLIR, LLVM, and/or Clang compiler development experience preferred.
- Familiarity with deep learning frameworks and NVIDIA GPUs preferred.
Benefits
- Base salary range of 184,000 USD to 287,500 USD, determined by location, experience, and comparable employee pay.
- Eligible for equity and benefits.
- Applications accepted at least until September 20, 2026.
- Existing vacancy.
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.