Ammar Ratnani is a software engineer specializing in systems and embedded work, with a decade of experience building performance-sensitive software close to hardware for companies like NVIDIA and research groups at Stanford and Georgia Tech. He has a proven track record improving performance—optimizing neural-network accelerators, boosting game performance on GeForce Now, and shrinking runtimes for critical layers like softmax and max-pooling. Comfortable across OS, hypervisor, and hardware boundaries, he’s implemented drivers, virtual memory, and compiler backends (LLVM) and has practical experience with cross-compilation, FPGA/Chisel flows, and embedded radio systems. A strong academic performer (Georgia Tech BS, Stanford MS) who wins hands-on competitions and ships production improvements, Ammar combines curiosity about “how things work” with the discipline to turn low-level insight into measurable system gains.
10 years of coding experience
2 years of employment as a software developer
Bachelor's degree, Computer Science, 4.0, Bachelor's degree, Computer Science, 4.0 at Georgia Institute of Technology
Master of Science - MS, Computer Science, 4.2, Master of Science - MS, Computer Science, 4.2 at Stanford University
Contributions:46 PRs, 199 pushes, 48 branches in 2 years 2 months
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