Aahil Mehta

Founder at Stealth Startup

San Francisco Bay Area United States
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Summary

👤
Senior
🎓
Top School
Aahil Mehta is a Senior Software Engineer in the Bay Area with nine years of experience building large-scale recommender and retrieval systems, currently researching foundational user modeling architectures at Google to improve ranking and predictive models. He has led JAX-based training infrastructure and driven multiple cross-team landings that delivered significant incremental ARR, and contributes to Keras/JAX integrations—optimizing kernels, data transfer, and TensorBoard reporting. Comfortable bridging research and production, he combines deep ML engineering with hands-on systems optimization and a background tutoring functional and JVM languages. Outside core product work, he consults in venture as a fellow, signaling a knack for spotting technical opportunities and translating them into impact.
code9 years of coding experience
job4 years of employment as a software developer
bookMaster of Engineering - MEng Computer Science, Master of Engineering - MEng Computer Science at Imperial College London
bookHigh School, High School at Blundell's School
bookSecondary school, Secondary school at The Cathedral and John Connon School
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Stackoverflow

Stats
1reputation
0reached
0answers
0questions
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Github Skills (7)

machine-learning10
deep-learning10
tensorflow10
jax10
python10
neural-network9
data-science8

Programming languages (2)

JavaScriptPython

Github contributions (5)

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keras-team/keras

May 2024 - Dec 2024

Deep Learning for humans
Role in this project:
userML Engineer
Contributions:3 reviews, 6 PRs, 4 comments in 6 months
Contributions summary:Aahil made several contributions focused on optimizing and extending the Keras backend for the JAX framework. These include speeding up `in_top_k` implementation, accelerating host-to-device data transfer, and adding support for JAX named scopes. They also addressed a bug related to rank computation and made improvements to the `TensorBoard` callback for reporting steps per second. Furthermore, the user allowed passing custom dataset adapters and fixed embedding issues.
deep-learningtensorflowneural-networksmachine-learningdata-science
Hilly12/dotfiles

Feb 2021 - Feb 2026

Contributions:9 pushes, 1 branch in 5 years 1 month
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