High-Performance Computing Engineer

1 day ago


New York, New York, United States Waymo Full time
Company Overview
Waymo is a leading autonomous driving technology company dedicated to making roads safer and more efficient. Our mission is to create the world's most trusted driver, providing unparalleled access to mobility while saving thousands of lives lost to traffic crashes.

Salary
The estimated base salary for this position is $158,000-$200,000 USD per year, reflecting our commitment to attracting top talent in the industry.

Job Description
This hybrid role requires a curious and talented individual to join our Compute Team, responsible for delivering the compute platform powering our autonomous vehicle software stack. As a compiler engineer, you will maximize performance of our neural networks by enhancing and extending our production-grade compiler.

Key Responsibilities:
  • Enhance and extend our production-grade compiler to maximize neural network performance.
  • Collaborate with hardware architects and model developers to develop a deep understanding of our unique neural network inference platform and neural networks.
  • Implement compiler support for novel features of our high-performance architecture.

Requirements:
  • Bachelor's degree in Computer Science or Electrical Engineering, or equivalent practical experience, plus 3+ years of industry experience; or Master's degree in Computer Science or Electrical Engineering, plus 1+ year of industry experience; or PhD in Computer Science or Electrical Engineering.
  • 1+ years of industry and/or academic experience with compilers and parallel computing.
  • 1+ years of industry and/or academic experience working with ML inference or linear algebra computations.
  • C++ programming skills.

Preferred Qualifications:
  • Python programming experience.
  • Experience with compilers for neural networks.
  • Knowledge of computer architectures used for neural network inference, and neural network performance characteristics.
  • Knowledge of the principles behind popular machine learning and neural network algorithms and applications.


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