Vivswan Shah
Member Of Technical Staff at Microsoft AI
New York City Metropolitan Area United States
Summary
👤
Senior🎓
Top SchoolVivswan Shah is a machine learning systems engineer with nine years of experience building low-latency, distributed deep learning infrastructure across industry and academia. He holds a PhD focused on real-time distributed deep learning for heterogeneous GPU/CPU/NPU clusters and has led a research lab that deployed secure, high-throughput pipelines and optimized models for hybrid analog-digital accelerators achieving nanosecond-scale inference. His industry roles span applied science and research engineering at Amazon, Scale AI, and Microsoft AI, working on GenAI, agentic systems, LLMs, and MLOps for production at scale. He combines hands-on systems work (CI/CD, Terraform, Ansible, Docker) with model-level expertise (distillation, pre-/mid-training, evaluation) and experience integrating novel photonic and hardware accelerators into ML stacks. Based in the New York City area, he often bridges academic collaborations with industry partners including Google X and the DoD, bringing a rare mix of hardware-aware model optimization and production ML infrastructure.
9 years of coding experience
5 years of employment as a software developer
Bachelor's degree Computer Science and Physics, Bachelor's degree Computer Science and Physics at Illinois CollegeDoctor of Philosophy - PhD Machine Learning System, Doctor of Philosophy - PhD Machine Learning System at Carnegie Mellon UniversityDoctor of Philosophy - PhD Machine Learning System, Doctor of Philosophy - PhD Machine Learning System at University of Pittsburgh
English, Hindi
Github Skills (40)
simulation10
python10
acceleration10
machine-learning10
photonics10
hardware10
numpy10
deep-learning10
gpu10
neural-network10
gpu-acceleration10
klayout10
eda9
autograd9
cad9
Programming languages (8)
Github contributions (5)
Vivswan/Tomasulo-Algorithm-Implementation
Oct 2021 - Oct 2022
Contributions:65 commits, 13 PRs, 64 pushes in 1 year
Vivswan/HackMIT-2019-Solution
Nov 2019 - Jul 2023
Contributions:2 PRs, 3 pushes, 4 branches in 3 years 8 months
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