Rishabh Bhargava - Director, ML at Together AI

Rishabh Bhargava

Director, ML at Together AI

San Francisco, California, United States

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Summary

🤩

Rockstar

🎓

Top School

Rishabh Bhargava is a seasoned machine learning leader and founder with 11 years of experience building data and ML products at the intersection of research and production. He co-founded Refuel.ai to deliver high-quality data rapidly and now leads ML efforts as Director, ML at Together AI in San Francisco. His background spans startups and enterprise roles—from early ML engineering at Primer to product and field leadership at Datacoral (acquired by Cloudera)—giving him deep expertise in data pipelines, MLOps, and scaling models. He contributes to open-source tooling for serverless Python on AWS, demonstrating attention to stability and dependency management in production systems. A former Stanford CS graduate TA for CS229, he pairs strong academic roots with practical leadership, mentoring teams that move from prototypes to deployed ML. Colleagues describe him as a pragmatic operator who blends product intuition with hands-on engineering to get messy data working at scale.

11 years of coding experience

9 years of employment as a software developer

Year Abroad Computer Software Engineering, Year Abroad Computer Software Engineering at Massachusetts Institute of Technology

Master of Engineering (MEng) Engineering, Master of Engineering (MEng) Engineering at University of Cambridge

Master’s Degree Computer Science, Master’s Degree Computer Science at Stanford University

Hindi

Github Skills (10)

version-control10

dependency-management10

aws-lambda10

aws10

py10

python10

package-management10

setuptools10

serverless9

boto9

Programming languages (1)

Python

Github contributions (5)

nficano/python-lambda

Apr 2020 - Jan 2021

A toolkit for developing and deploying serverless Python code in AWS Lambda.

Role in this project:

Backend Developer

Contributions:8 commits, 19 PRs, 21 pushes in 9 months

Contributions summary:Rishabh primarily focused on maintaining and updating the project's dependencies and versioning. Their contributions included adding missing packages to the `setup.py` file, bumping the project's version multiple times, and allowing for more up-to-date versions of the `boto3` library. This suggests a focus on ensuring the project's stability and compatibility with newer AWS services. They are also ensuring that the project is up-to-date with bug fixes from the dependencies.

deployingpython-codepythondevelopingaws-lambda

jamesrobertlloyd/dataset-space

Nov 2014 - Jun 2015

Contributions:34 commits, 1 push in 6 months

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