Sangamesh Ragate is a Principal Engineer based in Sunnyvale with nine years of experience building high-performance kernels and libraries for deep learning workloads. He has progressed from HPC research and performance analysis roles to leading parallel and distributed algorithm development at Cerebras Systems, with hands-on optimization for architectures like Intel Knights Landing and Xeon Phi. His background blends deep academic research—PAPI tool development and a Master’s in Computer Engineering—with pragmatic engineering that accelerates real-world DL frameworks such as PyTorch on specialized hardware. Known for squeezing performance out of unconventional accelerators, he bridges low-level systems work and scalable ML implementations. Colleagues rely on him for complex performance tuning and for translating research ideas into production-grade kernels that run on next-generation AI accelerators.
9 years of coding experience
13 years of employment as a software developer
BE Electronics & communication, BE Electronics & communication at M.S.Ramaiah Institute Of Technology
Master's degree Computer Engineering, Master's degree Computer Engineering at University of Tennessee, Knoxville
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Sangamesh Ragate - Principal Engineer at Cerebras Systems