Ritesh Patel
Senior Deep Learning Architect at NVIDIA
Sacramento, California, United States
Summary
👤
Senior🎓
Top SchoolRitesh Patel is a Senior Deep Learning Architect with 15 years of experience optimizing ML performance across GPUs and large-scale clusters, currently focusing on end-to-end training performance for LLMs at NVIDIA. He has led performance model development and software-hardware co-design at Google and Intel, building predictive cost models for core ML ops (GEMM, convs, fusions) and influencing TPU/GPU architecture decisions. Ritesh combines low-level kernel implementation expertise with system-level profiling to drive tangible speedups—authoring cycle-accurate simulators and highly optimized compute shaders earlier in his career. His background includes building control systems for precision manufacturing and translating hardware behavior into actionable software optimizations, a blend that helps him spot non-obvious bottlenecks across the stack. Based in Sacramento, he brings deep practical experience in performance pathfinding, sharding/scheduling strategies, and operation fusion techniques that accelerate production-scale ML training.
15 years of coding experience
14 years of employment as a software developer
Master of Science (M.S.) Electrical and Computer Engineering, Master of Science (M.S.) Electrical and Computer Engineering at University of California, Davis
English, Gujarati
Github Skills (11)
parallelization10
parallel-processing9
parallel8
accelerator8
openmp8
mpi8
infiniband8
cuda8
parallel-computing8
gpu7
petsc7
Programming languages (1)
Github contributions (2)
rapatel/filtick
Jul 2016 - Aug 2016
Contributions:4 pushes, 1 branch in 15 days
cudpp/cudpp
Feb 2011 - Feb 2013
CUDA Data Parallel Primitives Library
Contributions:38 commits in 2 years 1 month
cudampiinfinibandparallelgpu
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