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Agam Jain

Agam Jain

Founder of Tensorfuse, democratizing ML infrastructure with serverless GPUs

agamjn
San Francisco, California
Bangalore, Karnataka, India
Joined March 2024
Favicon imageagamjn.github.io
Favicon imageycombinator.com

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Summary

Agam Jain is a driven entrepreneur and developer, currently focused on making machine learning infrastructure more accessible and efficient. As the co-founder of Tensorfuse, a Y Combinator-backed startup, he is building tools to run serverless GPUs on the cloud, aiming to democratize AI technology for researchers and engineers. github+2
His professional journey reflects a strong foundation in computer vision and semiconductor technology, stemming from his education at IIT Roorkee and his tenure as a Systems Engineer at Qualcomm. During his time at Qualcomm, he was a computer vision researcher, where he contributed to a patent and co-authored a scientific publication. github+3
Agam has experience in the startup ecosystem, having been part of the founding team at Aerotime (YC W21), where he contributed to the company's initial growth and worked on a tool for managing qualitative user interviews. This experience solidified his passion for solving problems and building impactful products. linkedin+1
Beyond his technical and entrepreneurial pursuits, Agam has a creative and introspective side, enjoying hobbies such as playing Badminton, the Ukulele, and writing. He also believes in being passionate about problems rather than just tools, and advocates for consuming less and creating more. github+1

Work

Education

Writing

Display processing: scaling operation, feature detection, and pixel adjustment

September 3, 2024

Co-inventor on a patent focused on methods and devices for display processing, including receiving input images for scaling, detecting features, adjusting pixels, and processing output pixels to create an output image.

Favicon imagepatents.justia.com

Analytical model based estimation of line edge roughness induced VT variability in nanowire FETs

January 1, 2022

Co-authored a research paper published in Solid-State Electronics that explores an analytical model to estimate threshold voltage variability due to line edge roughness in nanowire FETs, showing improved accuracy and computational efficiency compared to previous models.

Favicon imagesciencedirect.com

Hobbies

Enjoys playing Badminton and the Ukulele, and also dedicates time to writing. github+1