Senior ML Compiler Engineer

Boston, MA · Job # 8685BK

Job Overview:


Our client is searching for a deep learning compiler engineer to build the compiler and software tool chain for deploying machine learning models on to a variety of photonics accelerators.

You will collaborate closely with engineers from architecture and research team etc. to scope out system/software/hardware requirements from chip up to algorithm level while engaging with hardware teams to understand the target hardware platform and its constraints like photonic circuits.


Your role:

  • Design, implement and test compiler features and capabilities related to IR infrastructure and compiler passes
  • Develop graph compiler optimizations like operator fusion, layout optimization, etc. that are customized to the different accelerators
  • Develop efficient custom operators for opto-electric pipeline and optimize data motion
  • Integrate open-sourced compiler technology into internal compiler infrastructure
  • Build performance tooling to evaluate, understand and improve ML performance of different models on different accelerators
  • Collaborate with cross functional agile teams of presale and hardware engineers to guide the direction of machine learning
  • Follow industry and academic developments in the ML compiler and algorithm domain for photonic quantization and gradient descents and provide performance guidelines and best practices for other partner teams

Ideal qualifications:

  • GPU programming (CUDA) and familiarity with deep learning stack (e.g., cuDNN, cuBLAS)
  • Experience with NVDLA and other accelerators etc.
  • Experience with open-source deep learning stacks (TVM, XLA, etc.)


  • 5+ years of experience in the field of compiler design and 2+ years of experience with deep learning
  • Experience with deep learning frameworks (e.g., Tensorflow, Pytorch etc.) and software stack (e.g., TensorRT, TVM, etc.)
  • Experience with ML accelerators and hardware architecture
  • Strong expertise in writing production quality C++ code
  • Comfortable and experienced in software development lifecycle - coding, debugging, optimization, testing, integration
  • Familiarity with parallelization techniques for ML acceleration
  • MS, or higher degree, in CS/CE/EE, or equivalent, in industry experience


Applicants must be authorized to work in the United States legally.


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