Arash Bakhtiari
Member Of Technical Staff at Microsoft AI
Redmond, Washington, United States
Summary
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Rockstar🎓
Top SchoolArash Bakhtiari is a research-focused software engineer with 13 years of experience building high-performance and edge AI systems, now a Member of Technical Staff at Microsoft AI. He holds a PhD in High Performance Computing and Parallel Algorithms and has driven production-grade optimizations across CPU, ARM, and custom graph-native architectures at companies like Blaize, Plumerai and Intel. Arash blends low-level expertise in C++, CUDA, SIMD and assembly with practical ML engineering—contributing OPT model support and custom kernels to the widely used DeepSpeed project. His background includes leading the Larq Compute Engine for binarized neural networks and hands-on work quantizing and tuning vision models for novel hardware. Based in Redmond, he pairs strong academic rigour with a track record of shipping high-impact, highly optimized inference engines and distributed training improvements.
13 years of coding experience
13 years of employment as a software developer
Visiting Scholar HPC Computational Science and Engineering, Visiting Scholar HPC Computational Science and Engineering at The University of Texas at AustinBachelor of Science (B.Sc.) Physics, Bachelor of Science (B.Sc.) Physics at Karlsruhe Institute of Technology (KIT)Doctor of Philosophy (PhD) High Performance Computing Parallel Algorithms Computational Fluid Dynamics , Doctor of Philosophy (PhD) High Performance Computing Parallel Algorithms Computational Fluid Dynamics at Technical University of MunichBachelor of Science (B.Sc.) Physics, Bachelor of Science (B.Sc.) Physics at Ludwig-Maximilians-Universität München
German, Persian, English
Stackoverflow
1reputation
0reached
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Github Skills (11)
transformers10
pytorch10
machine-learning10
deep-learning10
inference10
gpu10
parallelization10
python10
compression9
zeroth7
zero-code7
Programming languages (2)
Github contributions (5)
deepspeedai/DeepSpeed
Aug 2022 - Oct 2022
DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.
Role in this project:
ML Engineer
ML EngineerContributions:11 reviews, 30 commits, 17 PRs in 2 months
Contributions summary:Arash primarily contributed to adding and refactoring support for OPT models within the DeepSpeed library. Their work involved implementing custom MLP activation functions, modifying inference APIs, and adding unit tests for OPT models. Additionally, the user made improvements to the residual add and bias kernels, and address compatibility issues with older versions of the transformers library.
billion-parametersfinetuningtrainingmixture-of-expertszero
arashb/turbulent_lbm_multigpu
Apr 2013 - Mar 2020
Contributions:214 commits, 1 push in 6 years 11 months
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