Arash Mehraban is an AI/ML engineer with 11 years of experience building and deploying deep learning systems on CPU and GPU across cloud and HPC environments. He blends research-grade numerical PDE and high-order finite element expertise from a PhD with practical MLOps skills—containerization, Kubernetes, SageMaker, Terraform, and AWS services—for production-ready model training and inference. At ResMed he leads CNN and Transformer development and parallel training workflows, while earlier roles at CU Boulder involved scalable scientific computing on HPC clusters. His background in C/C++ and GPU/CPU programming gives him an edge in performance-critical model optimization and distributed computation. Based in San Diego, he pairs academic rigor with hands-on infrastructure engineering, often bridging the gap between numerical simulation code and modern ML pipelines.
11 years of coding experience
5 years of employment as a software developer
Doctor of Philosophy - PhD, Computer Sceince, Doctor of Philosophy - PhD, Computer Sceince at University of Colorado Boulder
MS, Mathematics, MS, Mathematics at East Tennessee State University
Total Lagrangian and current configuration compressible hyperelasticity
Contributions:103 commits, 1 PR, 101 pushes in 10 months
hyperelasticitylagrangiantotalcompressible
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Arash Mehraban - AI ML Engineer at University of Colorado Boulder