AI/ML Engineer with Mathematical Foundations
I build AI and machine learning systems grounded in mathematical principles — from deployed LLM products to optimization, probability, and dynamical systems.
PhD candidate in Topological Dynamics & Ergodic Theory, BITS Pilani.
My background is unusual for an AI/ML engineer: I spent years doing pure mathematics research — topological dynamics, ergodic theory, measure theory — before deliberately building toward applied ML and AI. That foundation means I don't just apply algorithms or wire up LLM APIs; I understand why they work, where they break, and how to design systems that are mathematically sound. I've since shipped Teachling — a live AI product built on React, Node.js, and Vertex AI — serving learners and instructors. I'm currently seeking AI/ML engineering or applied research roles where that rigour is an asset.
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