Staff Software Engineer, ML Compilers, Silicon

Google Google · Big Tech · New Taipei, Banqiao District, New Taipei City, Taiwan

Staff Software Engineer focused on ML Compilers for EdgeTPU, optimizing compiler quality, performance, and developing parallelization/scheduling algorithms for ML workloads, including generative AI models, on accelerators. Collaborates with architects and ML developers to transition research to user experiences.

What you'd actually do

  1. Work as part of the EdgeTPU compiler team, including analyzing and improving the compiler quality and performance on optimization decisions, correctness and compilation time.
  2. Develop parallelization and scheduling algorithms to optimize compute and data movement costs to execute ML workloads on the EdgeTPU.
  3. Work with EdgeTPU architects to design future accelerators, the hardware/software interface, and co-optimizations of the next generation EdgeTPU architectures.
  4. Work on efficient mapping of generative AI models and other key workloads into EdgeTPU instructions through the compiler.
  5. Work with Product Managers, Researchers in identifying key ML trends, future use cases, etc. Closely collaborate with ML model developers, researchers, and EdgeTPU hardware/software teams to accelerate the transition from research ideas to user experiences running on the EdgeTPU.

Skills

Required

  • C++
  • data structures/algorithms
  • compilers (optimization, parallelization, etc.)
  • software design and architecture
  • compiler development in the context of accelerator-based architectures

Nice to have

  • MLIR or LLVM
  • hardware-software codesign
  • optimizing ML model inference on device
  • CPU, GPU, or TPU

What the JD emphasized

  • compiler development in the context of accelerator-based architectures

Other signals

  • ML Compilers
  • EdgeTPU
  • ML workloads
  • generative AI models
  • accelerator-based architectures