Sr. Principal Software Engineer, ML Compiler Front-End (AI2139)

Engineering - Software San Jose, California


Sr. Principal Software Engineer, ML Compiler Front-End

Job ID- AI2139

Location: San Jose, CA (we are also open to remote work from within North America).

Job Description is looking for a Sr. Principal Software Engineer to join our world class team and lead the development of our state-of-the-art ML Compiler Front-End.  As the Technical Lead of our ML Compiler Front-End, you will get to work with leading-edge ML technologies.  You will also work with a talented team of engineers to optimize ML models so that they run efficiently on our Machine Learning System-on-a-Chip (MLSoc).

You will also have the opportunity to influence SiMa’s roadmap by proposing enhancements to both our software and future generations of the hardware.  


  • Serve as the Technical Lead of the ML Compiler Front-End team, collaborating cross-functionally with other Technical Leads.
  • Lead the analysis of ML applications and deep learning models to better understand their performance on the SiMa MLSoC, and further optimize them for performance. 
  • Lead efforts to enhance and support Front-End optimizations such as graph optimization, pruning, and quantization.
  • Lead efforts to participate in and contribute to the TVM open source community.
  • Lead efforts to improve the quality of the code base, such as code refactoring and documentation enhancement. 
  • Work closely with Program Management and Engineering Management to create project plans for the team’s activities, and provide regular status updates on how the team is progressing against its goals.
  • Contribute to SiMa’s roadmap by proposing new features for both our software products and  future generations of the MLSoC. 

Required Background

  • Ph.D. or M.S. in Computer Science or a related field with 10+ years of experience developing highly performant systems software.
  • Strong communication and leadership skills.
  • Strong programming skills in C, C++ or Python.
  • Strong background in algorithms and data structures.
  • Strong understanding of machine learning algorithms such as matrix multiplication and convolution.
  • Experience with deep learning frameworks such as TensorFlow, PyTorch and ONNX.
  • Good understanding of processor architecture.
  • Highly desirable: prior experience with TVM and deep learning quantization schemes.

Personal attributes:

Can-do attitude. Strong team player. Curious, creative and good at solving problems. Execution and results-oriented. Self-driven, Thinks Big and is highly accountable. Good communication skills.