Aditya Prasad

Software Engineer at Weights & Biases

Austin, Texas, United States
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Summary

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Rockstar
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Top School
Aditya Prasad is a software engineer with 10 years of experience, currently building full-stack features at Weights & Biases after earlier development roles at Delphix and internships focused on test automation and UX-driven front-end work. He holds a Computer Science degree from UT Austin and brings practical experience across backend Java services, PostgreSQL schema work, and JavaScript front-end frameworks like Knockout.js. Comfortable shipping across the stack, he has implemented production notification systems, refactored test frameworks, and presented features company-wide—demonstrating both technical depth and clear communication. Based in Austin, he’s passionate about learning development lifecycles at companies of all sizes and translating UX collaboration into simpler developer-facing workflows. A detail that sets him apart is his blend of QA-focused automation experience and full-stack feature delivery, which helps him anticipate reliability and user experience issues early in the cycle.
code10 years of coding experience
job1 year of employment as a software developer
bookBachelor’s Degree, Computer Science, Bachelor’s Degree, Computer Science at The University of Texas at Austin
bookInternational Baccalaureate, Mathematics, Physics, Computer Science, English, French, International Baccalaureate, Mathematics, Physics, Computer Science, English, French at Bellaire High School
languagesEnglish, French, Hindi, Tamil
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Github Skills (22)

pytorch10
visualization10
data-science10
machine-learning10
reinforcement-learning10
hyperparameter-optimization10
keras10
data-versioning10
mlops10
deep-learning10
api10
tensorflow10
ai10
hyperparameter-tuning10
collaboration10

Programming languages (2)

JavaScriptPython

Github contributions (5)

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Contributions:45 pushes in 5 months
AdityaPrasad1/CS-314

Sep 2015 - Jan 2016

Contributions:19 pushes, 1 branch in 4 months
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Aditya Prasad - Software Engineer at Weights & Biases