Janet Schneider
Software Engineer at OctoML
United States
Summary
🤩
Rockstar🎓
Top SchoolJanet Schneider is a software engineer and systems architect with nine years of experience building AI, mixed reality, sensor, storage, and security solutions. She combines hands-on expertise in embedded development, custom silicon and superconducting logic with deep systems knowledge—drivers, storage architectures, and security devices—to ship robust, maintainable products. A proven leader, she has recruited and led diverse multinational teams and translated complex hardware-software designs into production-ready systems. Janet is an active open-source contributor, notably improving runtime and resource management for the Apache TVM project to better utilize Hexagon accelerators via VTCM pools and DMA/thread controls. Her background in computer science and mathematics underpins a pragmatic, performance-focused approach that balances cutting-edge research with operational reliability.
9 years of coding experience
B.S., Computer Science, Mathematics, B.S., Computer Science, Mathematics at Gonzaga University
Github Skills (14)
hex10
memory-management10
hexagonal-architecture10
c-language10
cprogramming-language10
performance-optimization10
multithreading10
concurrency10
compiler-compiler9
compiler9
deep-learning8
machine-learning8
gpu8
opencl7
Programming languages (2)
Github contributions (5)
apache/tvm
Sep 2022 - Jan 2023
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Role in this project:
Back-end Developer & Performance Engineer
Back-end Developer & Performance EngineerContributions:114 reviews, 20 commits, 31 PRs in 3 months
Contributions summary:Janet made significant contributions to the runtime environment, particularly focusing on resource management for the Hexagon architecture. Their work involved implementing and refining buffer management, including the introduction of VTCM memory pools and separate buffer management for RPC and runtime operations. Furthermore, they added support for thread and DMA resource management, improving performance by enabling hardware resource utilization and control. The user also made key improvements to the device API, adding APIs for both runtime and RPC buffer management.
metalvulkancompilertensoropencl
janetsc/tvm
Aug 2022 - Apr 2023
Open deep learning compiler stack for cpu, gpu and specialized accelerators
Contributions:140 pushes, 61 branches in 7 months
cpugpu-programminggpu-accelerationtvmdeep-learning
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