Igor Gitman
Senior Applied Scientist at NVIDIA
Greater Seattle Area United States
Summary
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Rockstar🎓
Top SchoolIgor Gitman is a Senior Applied Scientist with eight years of experience building and optimizing deep learning systems at NVIDIA and Microsoft, currently based in the Greater Seattle Area. He blends research rigor from a Machine Learning master's at Carnegie Mellon with hands-on MLOps and backend engineering, contributing to high-impact open-source toolkits like NVIDIA/OpenSeq2Seq. His work spans model architecture tweaks, training-loop optimizations, and large-batch training techniques—skills honed during internships that contributed to LARS and authoritative analyses of normalization methods. Comfortable moving ideas from theory to production, he has a track record of improving training performance on single GPUs and scaling experiments for industry-scale workloads. Colleagues rely on him for pragmatic solutions that bridge experimental ML research and reliable production pipelines.
8 years of coding experience
3 years of employment as a software developer
Master’s Degree, Machine Learning, Master’s Degree, Machine Learning at Carnegie Mellon UniversityLomonosov Moscow State University
Russian, English
Github Skills (5)
tensorflow10
dropout9
model-optimization9
batch-normalization9
machine-learning8
Programming languages (3)
Github contributions (5)
NVIDIA/OpenSeq2Seq
Apr 2018 - Jul 2018
Toolkit for efficient experimentation with Speech Recognition, Text2Speech and NLP
Role in this project:
Back-end Developer & MLOps Engineer
Back-end Developer & MLOps EngineerContributions:3 releases, 373 commits, 120 PRs in 3 months
Contributions summary:Igor was involved in debugging and optimizing the codebase, specifically addressing issues in the data processing pipeline and improving the performance of training on a single GPU. They added and modified parameters related to batch normalization and dropout, showing a focus on model architecture and performance. The user made changes to the training loop, suggesting involvement in the machine learning pipeline.
nlpexperimentationseq2seqspeech-to-textrecognition
NVIDIA/NeMo-Skills
Feb 2024 - Mar 2025
A project to improve skills of large language models
Contributions:445 reviews, 414 PRs, 711 pushes in 1 year 1 month
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