Jacky Cao
Software Engineer at Google
Seattle, Washington, United States
Summary
🤩
Rockstar🎓
Top SchoolJacky Cao is a software engineer based in Seattle with six years of experience building high-performance ML backends and systems software. Currently at Google, he contributes deep expertise in PyTorch/XLA integration—adding operations like inverse and logsumexp and improving XLA's stability and performance for TPU execution. His background includes co-op stints at Samsung and Nano-Lit, giving him practical experience across large-scale product engineering and embedded/system-focused projects. Jacky combines C++ systems-level development with machine learning tooling, often working on shape functions and Dynamo/XLA interoperability that meaningfully accelerate model execution. Known for precise, test-driven contributions to widely used open-source projects like PyTorch, he brings both production rigor and a researcher’s attention to numerical correctness.
6 years of coding experience
1 year of employment as a software developer
Bachelor of Science - BS, Computer Science, Bachelor of Science - BS, Computer Science at Simon Fraser University
Github Skills (20)
pytorch10
c-language10
python10
operation10
tensorrt10
machine-learning10
deeplearning-ai10
deep-learning10
tensorflow10
xla10
tensor10
cprogramming-language10
linear-algebra10
testing9
aws-dynamodb9
Programming languages (4)
Github contributions (5)
pytorch/xla
Feb 2020 - Jan 2023
Enabling PyTorch on XLA Devices (e.g. Google TPU)
Role in this project:
Back-end Developer
Back-end DeveloperContributions:3413 reviews, 899 commits, 1969 PRs in 3 years
Contributions summary:Jacky's primary contribution focused on implementing and testing new operations, specifically "inverse" and "logsumexp," within the PyTorch/XLA framework. Their work involved modifying core C++ files related to matrix operations and operations, as well as creating tests for the added functionality. The changes also included additions to the aten_xla_type and tensor_methods files, indicating contributions to the bridge between PyTorch and XLA.
pytorchxladeep-learningtpucompiler
pytorch/pytorch
Feb 2020 - Jan 2023
Tensors and Dynamic neural networks in Python with strong GPU acceleration
Role in this project:ML Engineer
ML EngineerContributions:246 reviews, 24 commits, 82 PRs in 2 years 11 months
Contributions summary:Jacky primarily contributes to the PyTorch project, focusing on enhancements and fixes related to the XLA (XLA for PyTorch) backend, demonstrating a specialization in machine learning and optimization. Their work involves adding shape functions for various operations, addressing issues in the XLA integration with Dynamo, and improving the performance and stability of XLA-related tests. These contributions aim to improve the integration of PyTorch with the XLA compiler for more efficient model execution.
pythongpu-accelerationdeep-learninggpunumpy
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