Aditya Paliwal
Member Of Technical Staff at xAI
San Francisco, California, United States
Summary
👤
Senior🎓
Top SchoolAditya Paliwal is a Member of Technical Staff at xAI with 11 years of experience building AI-driven systems, distributed computing platforms, and production-grade software. He previously held roles as a Quantitative Researcher at Citadel Securities and an AI Resident at Google, blending research rigor with low-latency, high-reliability engineering. Based in San Francisco, he brings deep expertise in backend and DevOps, demonstrated by contributions to replicate/keepsake where he added YAML configuration support across Python and Go implementations and optimized Go CLI checkout and tarball extraction. His work shows a practical focus on backward compatibility and reducing code duplication while improving developer workflows for ML versioning. Trained with a Master’s in Computer Science from IIIT Bangalore, he moves seamlessly between prototyping novel ML ideas and hardening them for production. Colleagues appreciate that he pairs algorithmic insight with pragmatic engineering—often surfacing small UX and tooling improvements that materially speed team delivery.
12 years of coding experience
3 years of employment as a software developer
Master's Degree, Computer Science, Master's Degree, Computer Science at International Institute of Information Technology Bangalore
English, Hindi
Stackoverflow
1,819reputation
142kreached
40answers
18questions
permutation
top-5%
Github Skills (14)
version-control10
go10
python10
yaml10
permutation9
machine-learning9
object-detection6
algorithm6
method-chaining6
python-itertools6
tensorflow6
classification6
dockers5
docker5
Programming languages (5)
Github contributions (5)
replicate/keepsake
Nov 2020 - Jan 2021
Version control for machine learning
Role in this project:
Back-end & DevOps Engineer
Back-end & DevOps EngineerContributions:14 reviews, 16 commits, 5 PRs in 1 month
Contributions summary:Aditya primarily focused on enhancing the project's configuration handling, adding support for `.yml` configuration files across both the Python and Go implementations. This involved modifying existing code to accommodate the new file extension, ensuring backward compatibility, and reducing code duplication. The user also worked on improving the Go CLI by implementing features like individual file or directory checkout. Furthermore, they introduced functionalities to extract specific files from tarballs, optimizing the checkout process.
machine-learningversion-control
VastoLorde95/configs
Feb 2022 - Feb 2026
Contributions:48 pushes, 1 branch in 4 years
Find and Hire Top DevelopersWe’ve analyzed the programming source code of over 60 million software developers on GitHub and scored them by 50,000 skills. Sign-up on Prog,AI to search for software developers.