Cameron Quilici
Member Of Technical Staff at SemiAnalysis
Houston, Texas, United States
Summary
🤩
Rockstar🎓
Top SchoolCameron Quilici is a machine learning and AI engineer with six years of software experience and dual BS degrees in Computer Science and Applied Mathematics from Texas A&M. He has built production AI infrastructure—designing scalable model deployment APIs, CI/CD pipelines, and dynamic model caching for Kubernetes environments—and driven MLCommons inference benchmarking and inference workflows. His background blends research (an undergraduate thesis on GraphBLAS graph clustering) with hands-on systems work in cloud and HPC tooling, Terraform/Ansible automation, and backend API design. At Hewlett Packard Enterprise and SemiAnalysis he translated customer signals into production ML solutions using transcription, LLM summarization, and topic analysis. Cameron’s strength is working at the intersection of rigorous mathematics and practical engineering to shrink model deployment time and improve performance, with a particular interest in graph algorithms and scientific computing.
6 years of coding experience
2 years of employment as a software developer
Bachelor of Science - BS, Computer Science, Applied Mathematics, 3.956 (Alumni), Bachelor of Science - BS, Computer Science, Applied Mathematics, 3.956 (Alumni) at Texas A&M UniversityThe Woodlands High School
Github Skills (50)
pytorch10
test-coverage10
benchmark10
distributed-training10
llama10
machine-learning10
inference10
amd10
llm10
keras10
nvidia10
hyperparameter-optimization10
openai10
ai10
cuda10
Programming languages (7)
Github contributions (5)
cquil11/LAGraph
Oct 2023 - Apr 2024
This is a library plus a test harness for collecting algorithms that use the GraphBLAS. For test coverage reports, see https://graphblas.org/LAGraph/ . Documentation: https://lagraph.readthedocs.org
Contributions:303 pushes, 15 branches in 6 months
SemiAnalysisAI/InferenceX
Oct 2025 - Jul 2026
Open Source Continuous Inference Benchmark Research Platform — Kimi K3 2.8T, MiniMax M3, DeepSeekv4, GLM5 - GB200 NVL72 vs MI355X vs B200 vs GB300 NVL72 & soon™ TPUv6e/v7/Trainium2/3 | 开源持续推理基准研究平台 — Kimi K2.7-Code、MiniMax M3、DeepSeekv4、GLM5 - GB200 NVL72 vs MI355X vs B200 vs GB300 NVL72，即将推出™ TPUv6e/v7/Trainium2/3
Contributions:88 reviews, 124 PRs, 1256 pushes in 9 months
inferenceminimaxaibenchmarkllm
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