Aaditya Nair
Production Engineer at Meta
London, England, United Kingdom
Summary
👤
Senior🎓
Top SchoolAaditya Nair is a Production Engineer with 12 years of experience building secure, reliable infrastructure at scale, currently helping manage over 9 million servers on Meta’s Host Management team. His background blends hands-on production engineering with information security—designing secure policies, onboarding Vault and BitWarden, and integrating identity systems like Okta for trading and crypto use cases at Tower Research Capital. He pairs academic research on erasure coding for distributed storage (award-winning work) with practical contributions to open-source projects like sympy, where he improved core math logic and bug fixes. Comfortable in both low-level infrastructure and high-scale operational workflows, he focuses on observability, secure host lifecycle management, and minimizing cross-service risks. Colocated in London, he brings a research-informed mindset to production problems, often finding elegant, correctness-first fixes that improve robustness across massive fleets.
12 years of coding experience
7 years of employment as a software developer
12th Graduate, 12th Graduate at Delhi Public School BhilaiBTech+ MS (By Research) in Computer Science Erasure Coding for Distributed Storage, BTech+ MS (By Research) in Computer Science Erasure Coding for Distributed Storage at International Institute of Information Technology Hyderabad (IIITH)
French, Malayalam, Hindi, English
Github Skills (11)
mathematics10
computer-algebra10
math10
python10
computer-algebra-system10
data-structure9
algorithm9
data-structures9
algorithms9
refactoring8
testing8
Programming languages (7)
Github contributions (5)
sympy/sympy
Jan 2015 - Apr 2015
A computer algebra system written in pure Python
Role in this project:
Back-end Developer
Back-end DeveloperContributions:13 commits, 5 PRs, 45 comments in 2 months
Contributions summary:Aaditya primarily focused on improving the `sympy/sympy` repository by addressing code quality, fixing bugs, and adding features. They refactored code to utilize the `sympy.core.compatibility.reduce` function instead of `functools.reduce`, and fixed a dependency issue with the pyglet library. The user also implemented `is_prime` functionality for the `Mul` and `Pow` classes, improving sympy's capabilities for mathematical analysis. These changes indicate a focus on the underlying logic and functionality of the computer algebra system.
mathpythonsciencecomputer-algebra-systemalgebra
AadityaNair/MangaDownload
Apr 2014 - Dec 2014
Contributions:75 commits in 7 months
pythonmangapython-scriptanime
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