Principal GPU Compute Architect — AI Stack & MLIR

Morr0

San Francisco (CA)

Presencial

USD 180 000 - 240 000

Tempo integral

há 37 horas
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Resumo da oferta

Morr0 is seeking a Principal AI Compute Architect to lead the design of a new GPU/AI software stack, spanning compilers, runtimes and GPU execution strategies. The role focuses on optimizing kernels, SIMT execution and memory scheduling while collaborating with silicon and software teams on co-design.

The ideal candidate will have deep expertise in GPU compilers, CUDA, and AI runtimes, with a track record of influencing code generation and performance at scale in production environments.

Qualificações

  • Significant experience in GPU architecture, compilers or ML systems.
  • Strong C/C++ expertise and understanding of CUDA/SIMT.
  • Experience with LLVM/MLIR, GPU kernel optimization or AI runtimes.
  • Solid performance profiling, debugging and architectural decision-making skills.
  • Ability to work across multiple layers of the AI compute stack.

Responsabilidades

  • Shape the architecture of a new GPU/AI software stack.
  • Drive performance optimization across compilers, runtimes, kernels and hardware.
  • Influence LLVM/MLIR, code generation and GPU execution strategy.
  • Optimize scheduling, memory utilization and SIMT execution.
  • Work closely with silicon and software teams on hardware/software co-design.
  • Help scale the platform for production AI inference.

Conhecimentos

GPU architecture
C/C++ expertise
CUDA/SIMT
LLVM/MLIR
Performance profiling

Descrição da oferta de emprego

Morr0 is seeking a Principal AI Compute Architect to lead the design of a new GPU/AI software stack, spanning compilers, runtimes and GPU execution strategies. The role focuses on optimizing kernels, SIMT execution and memory scheduling while collaborating with silicon and software teams on co-design.

The ideal candidate will have deep expertise in GPU compilers, CUDA, and AI runtimes, with a track record of influencing code generation and performance at scale in production environments.

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