Software Engineer, Compilers and Distributed Runtime Systems
Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Auckland, New Zealand; Mountain View, CA, USA; Seattle, WA, USA.
- Bachelor's degree in Electrical Engineering or Computer Science, or equivalent practical experience.
- 5 years of experience with software development and data structures/algorithms.
- 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
- Experience with compiler technologies, distributed systems, and communication libraries (e.g. MPI).
- PhD in Electrical Engineering or Computer Science.
- Experience programming in C++ and Python.
- Experience with compiler intermediate representations (e.g., MLIR, XLA, HLO).
- Experience with program generation and synthesis, and behavioral simulators.
- Experience with system-level hardware/software co-design.
- Excellent communication, teamwork, and problem-solving skills.
About the job
In this role, you will develop tools to enable the co-design of ML models with both accelerators and system architecture. You'll work with an experienced team of researchers to develop compiler technologies and runtime support for modeling ML inference performance.
For the United States: The US base salary range for this full-time position is $157,000-$235,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google.
- Build cost models that estimate the system performance of ML models.
- Design and build compiler techniques for automating the partitioning and distribution of ML models.
- Design and build runtime systems support in the OpenXLA framework to evaluate the effectiveness of above compiler transformations.
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