Mathias Insley
Software Engineer at Rivian and Volkswagen Group Technologies
San Francisco Bay Area United States
Summary
🤩
Rockstar🎓
Top SchoolMathias Insley is a versatile software engineer with six years of experience building embedded systems, web applications, and AI infrastructure across startups and industry leaders like Rivian/Volkswagen and DNA Script. He bridges hardware-near C++ and embedded Linux work with web front-ends in TypeScript and backend services, and has applied that cross-domain skillset to production DNA synthesis hardware and autonomous-vehicle software. An active open-source contributor, he augmented the Rust-based Burn deep-learning framework with practical features—LSTM/GRU modules, gradient clipping, and tensor pretty-printing—showing an emphasis on tooling that makes ML research and debugging more productive. Comfortable leading projects and teams, he has managed large student teams at JHU to deliver scalable epidemiological simulations and translated domain needs into clear product requirements as a software product owner. Based in the San Francisco Bay Area with a Materials Science & Engineering background from Johns Hopkins, he brings a blend of experimental science rigor and pragmatic software engineering to complex, multidisciplinary problems.
7 years of coding experience
6 years of employment as a software developer
Bellarmine College PreparatoryMaterials Science and Engineering, Materials Science and Engineering at Johns Hopkins Whiting School of Engineering
Github Skills (17)
autodiff10
machine-learning10
deeplearning-ai10
deep-learning10
neural-network10
tensor10
rust10
concurrency7
auto-tuning6
llm5
pytorch4
onnx4
ndarray4
wasmtime3
webgpu3
Programming languages (4)
Github contributions (5)
tracel-ai/burn
Jan 2023 - Feb 2025
Burn is a next generation tensor library and Deep Learning Framework that doesn't compromise on flexibility, efficiency and portability.
Role in this project:
Back-end Developer
Back-end DeveloperContributions:52 reviews, 21 PRs, 121 comments in 2 years 1 month
Contributions summary:Mathias contributed significantly to the `burn` deep learning framework, focusing on core functionality. They implemented a pretty-printing feature for tensors, enhancing debugging and visualization capabilities. Further contributions included gradient clipping, a feature vital for mitigating exploding gradients during training, and the development of LSTM and GRU modules for recurrent neural networks. Finally, they added the split and remainder operations, which add to the framework's completeness.
deep-learningtensorautodiffmachine-learningrust
agelas/burn
Mar 2023 - Dec 2025
BURN: Burn Unstoppable Rusty Neurons
Contributions:199 pushes, 20 branches in 2 years 9 months
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