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What you will be doing:
Analyze the performance of application code running on NVIDIA GPUs with the aid of profiling tools.
Identify opportunities for performance improvements in the LLVM based compiler middle end optimizer.
Design and develop new compiler passes and optimizations to produce best-in-class, robust, supportable compiler and tools.
Interact with Open-source LLVM community to ensure tighter integration.
Interact with Architecture teams to influence hardware evolution
Work with geographically distributed compiler, hardware and application teams to oversee improvements and problem resolutions.
Be part of a team that is at the center of deep-learning compiler technology spanning architecture design and support through higher level languages.
What we need to see:
B.S, M.S or Ph.D. in Computer Science, Computer Engineering, or related fields (or equivalent experience).
5+ years experience in Compiler Optimizations such as Loop Optimizations, Inter-procedural optimizations and Global optimizations.
Excellent hands-on C++ programming skills.
Understanding of any Processor ISA (GPU ISA would be a plus).
Strong background in software engineering principles with a focus on crafting robust and maintainable solutions to challenging problems.
Good communication and documentation skills and self-motivated.
Ways to stand out from the crowd:
Masters or PhD preferred
Experience in developing applications in CUDA or other parallel programming language.
Deep understanding of parallel programming concepts.
LLVM, MLIR and/or Clang compiler development experience.
Familiarity with deep learning frameworks and NVIDIA GPUs.
You will also be eligible for equity and .
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