Summary
Carlos Fernandez is a Senior Principal Performance Engineer with over 20 years of deep expertise in AI/HPC, systems architecture, and large-scale performance optimization across CPUs, GPUs, and ASICs. He has driven performance evaluation, code tuning, and pre-release hardware bringup on some of the world’s largest systems, blending hands-on kernel-to-application debugging with strategic technical team leadership. His career spans top-tier organizations—TACC, Intel, AWS, AMD, Habana, and Arm—where he built performance prediction methodologies, acceptance benchmarks, and resource-monitoring toolchains for production deployments. Comfortable with C/C++, Fortran, Python, MPI/OpenMP and parallel file systems like Lustre and Weka, he particularly excels at translating low-level architectural behavior into actionable optimizations. Based in Austin, he combines academic rigor (PhD) with practical results in exploratory projects and large-scale debugging that often surface new bottlenecks before they reach customers. A less obvious strength is his repeated role in early-stage hardware/software co-design and bringup, making him a go-to engineer when systems are most fragile and most critical.
11 years of coding experience
20 years of employment as a software developer
Master of Philosophy (MPhil) Physics, Master of Philosophy (MPhil) Physics at Universidad de Santiago de Compostela
Doctor of Philosophy (PhD), Doctor of Philosophy (PhD) at Cranfield University