Suraj Subramanian

Menlo Park, California, United States
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Summary

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Rockstar
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Top School
Suraj Subramanian is a full-stack machine learning engineer and Developer Advocate with a decade of experience building and deploying ML systems across finance and healthcare and now educating the PyTorch community. He combines hands-on MLOps expertise—particularly in distributed training with DDP, multi-GPU/multi-node workflows, and production-ready tooling—with a talent for translating complex AI topics to broad audiences, having reached 20 million developers across 84 countries. His open-source contributions span high-profile PyTorch repos and practical guides like the Llama cookbook, reflecting both low-level training optimizations and end-to-end model integration. Guided by a vision to use AI for sustainable community impact, he helps companies and startups adopt generative AI in traditional workflows while maintaining a pragmatic, deployment-first mindset.
code10 years of coding experience
bookUniversity of Mumbai
bookMasters, Information Science, Masters, Information Science at University of Pittsburgh
languagesTamil, Hindi, English
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Github Skills (24)

transformers10
pytorch10
slurm10
python10
ddp10
llama10
data-parallel10
machine-learning10
multiple-gpu10
reinforcement-learning10
data-parallelism10
huggingface10
mlops10
multi-gpu10
wandb10

Programming languages (8)

TypeScriptJavaRJavaScriptGoHTMLJupyter NotebookPython

Github contributions (5)

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meta-llama/llama-cookbook

Feb 2024 - Dec 2024

Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Role in this project:
userFull-stack Developer
Contributions:10 reviews, 34 PRs, 31 pushes in 9 months
Contributions summary:Suraj appears to have been involved in the restructuring of the repository's file organization and updating the main README. They added new notebooks to the quickstart guide, specifically for running Llama2 on Hugging Face transformers, and consolidated images into a top-level folder. The commit also included changes to the code differences of a notebook, showcasing work on running Llama models using the Hugging Face transformers library. These changes suggest involvement in both the front-end documentation and backend model integration.
aifinetuninglangchainllamallama2
pytorch/examples

Sep 2022 - Nov 2022

A set of examples around pytorch in Vision, Text, Reinforcement Learning, etc.
Role in this project:
userMLOps Engineer
Contributions:31 reviews, 14 commits, 11 PRs in 2 months
Contributions summary:Suraj primarily contributes to setting up and configuring distributed training environments for PyTorch models, specifically using DDP (DistributedDataParallel). Their work focuses on creating scripts and configurations for multi-GPU and multi-node training using tools like `torchrun` and SLURM. They integrate features like snapshotting and resuming training, enhancing the training workflow. Furthermore, they introduce minGPT-based training, demonstrating expertise in distributed training and potentially automated model deployment.
pytorchvisiondeep-learningreinforcement-learningreinforcement
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Suraj Subramanian