Senior Compiler Optimization Engineer - MLIR

NVIDIA•Redmond, WA

10d

About The Position

NVIDIA is seeking an experienced Compiler Optimization Engineer for its Compute Compiler Team. This role involves delivering features and improvements to CUDA and other compute compilers to enhance the performance of NVIDIA GPUs for various computational workloads, including deep learning, scientific computation, and self-driving cars. The successful candidate will be a key member of a team focused on a core compiler component for accelerating general-purpose computation on GPUs, working with top minds in GPU computing and systems software. The role offers the opportunity to see your work directly impact the performance of applications used by HPC and DL developers.

Requirements

B.S, M.S or Ph.D. in Computer Science, Computer Engineering, or related fields (or equivalent experience).
8+ 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.

Nice To Haves

Masters or PhD preferred
Experience in developing applications in CUDA or other parallel programming language.
Deep understanding of parallel programming concepts.
MLIR, LLVM and/or Clang compiler development experience.
Familiarity with deep learning frameworks and NVIDIA GPUs.

Responsibilities

Analyze the performance of application code running on NVIDIA GPUs with the aid of profiling tools.
Identify opportunities for performance improvements in the MLIR/LLVM based compiler middle end optimizer.
Identify and implement novel ideas in the compilation pipeline to enable overall best-in-class performance of AI workloads.
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.
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.