Matthew Bonanni

Machine Learning Engineer at Red Hat

Cambridge, Massachusetts, United States
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Summary

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Matthew Bonanni is a machine learning engineer who leverages a PhD in mechanical engineering and nine years of cross-domain engineering experience to accelerate large language model inference at Red Hat via vLLM. His academic work on massively-parallel large-eddy simulations for rocket and scramjet propulsion gave him deep HPC, C++, and CUDA expertise, and he has repeatedly translated that research into production-grade speedups and models during CBRE fellowships at multiple NASA centers. Prior roles at SpaceX, iRobot, and GE show a practical engineering instinct—designing hardware, automation tools, and test regimes that cut cycle time and boosted reliability. Comfortable at the intersection of high-performance simulation and ML systems, he brings a rare blend of fluid dynamics research, systems programming, and deployment experience to inference optimization.
code9 years of coding experience
job3 years of employment as a software developer
bookHigh School, High School at La Salle Institute
bookBS, summa cum laude, Mechanical Engineering, GPA 3.99/4.00, BS, summa cum laude, Mechanical Engineering, GPA 3.99/4.00 at Northeastern University
bookDoctor of Philosophy - PhD, Mechanical Engineering, Doctor of Philosophy - PhD, Mechanical Engineering at Stanford University
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Stackoverflow

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Github Skills (35)

pytorch10
llama10
inference10
tpu10
amd10
llm10
openai10
cuda10
gpt10
transformer10
meta-analysis9
tracks9
solver8
transport7
modeling-tool7

Programming languages (5)

CSSC++GoPythonCuda

Github contributions (5)

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MatthewBonanni/Wildfire-TPU

Oct 2019 - Apr 2020

TensorFlow implementation of percolation wildfire model
Contributions:13 PRs, 176 pushes, 13 branches in 6 months
percolationdeep-learningmachine-learningwildfiretensorflow
IhmeGroup/cantera

May 2020 - Sep 2022

Chemical kinetics, thermodynamics, and transport tool suite
Contributions:1 PR, 6 pushes, 2 branches in 2 years 4 months
pythonchemicalcytoscapejsmeta-analysisdiscrete-event-simulation
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