GPU Performance Tooling Engineer

Rivos Inc. Logo

Rivos Inc.

๐Ÿ“Remote - United States, Canada

Summary

Join Rivos and contribute to improving the Deep Learning ecosystem by developing and enhancing the Perfetto framework. This role involves designing and implementing features to simplify performance measurement for internal and external users. You will work on underlying libraries and drivers for performance data collection, ensuring minimal overhead. The position requires expertise in systems software, GPU performance tools, and the Perfetto framework. You'll collaborate with industry veterans, learn valuable skills, and contribute to open-source projects. This role offers opportunities for professional growth and collaboration within a fast-paced environment.

Requirements

  • Experience with Perfetto profiling framework
  • Ability to write code in C or C++
  • Experience with Protobuf
  • Understanding of computer architecture
  • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment
  • Excellent skills in problem solving, written and verbal communication
  • Strong organization skills, and highly self-motivated
  • Ability to work well in a team and be productive under aggressive schedules
  • Bachelorโ€™s, Masterโ€™s, or PhD in Computer Engineering, Software Engineering or Computer Science

Responsibilities

  • Develop and modify the Open Source Perfetto framework to enable software developers to improve performance of their code
  • Work on underlying libraries and drivers to enable performance data collection
  • Ensure performance monitoring overhead is minimized
  • Build tooling to facilitate measuring performance in different scenarios (on simulators, FPGAs, or real hardware)
  • Write unit tests and benchmark tools to validate the performance and correctness of your changes
  • Stay current with advancements in the field

Preferred Qualifications

  • Experience with profiling and optimizing low-level performance (memory bandwidth, latency, throughput) on GPU architectures
  • Familiarity with deep learning frameworks (TensorFlow, PyTorch, etc.)
  • Ability to write code in Rust
  • Coursework or experience with Machine Learning algorithms

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