ML Research & Engineering

Building intelligent systems with rigorous research and scalable engineering

About Me

I'm a Machine Learning Engineer at Google, developing the ML platform for Google Pay. My work spans the full ML lifecycle, from foundational research to production systems at scale. I've been immersed in the generative AI space for quite a while and closely follow its rapid developments.

Previously at Jio AICoE, I led initiatives on improving reasoning in small language models and built real-time computer vision systems. I worked across the ML spectrum - from training models to deployment, be it as REST APIs or on edge devices while also building expertise in MLOps and ML infrastructure.

Before Jio, I was a Machine Learning Research Assistant at skit.ai, where I worked on text-to-speech systems. I also interned at Hike Messenger, developing a real-time 3D avatar system. I've also had stints at a few other startups, each adding something new to my ML toolkit.

I'm an active open source contributor, participating in Google Summer of Code both as a student and mentor, and contributing to Facebook's Pysa as an MLH Fellow. Hackathons have been my creative playground, with wins including Smart India Hackathon where I built solutions for Government of Goa.

I see machine learning as modern alchemy, transforming raw data into intelligence through mathematical transmutation. In this pursuit, I follow the principle of equivalent exchange: meaningful insights require rigorous work and careful thought. Yet I've learned that our models possess emergent behaviors that transcend their mathematical foundations - a kind of computational essence that defies complete explanation. This mysterious element is what transforms mere calculation into something that appears genuinely intelligent, reminding us that even in our most advanced formulas, there remains something we cannot fully quantify (yet).

Featured Projects

Poor Man's Rekognition

Built an open-source alternative to Amazon's Rekognition service during Google Summer of Code. Scene text detection with TextBoxes++, text recognition with CRNN, scene classification with EfficientNet B7, object detection with YOLOv3, and face detection with RetinaFace. All models served via TensorFlow Serving with Django REST APIs.

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Real-time 3D Avatar Generation

Built real-time 3D avatar generation system at Hike Messenger. Used TensorFlow.js and Facemesh to generate 3D head mesh, Position Map Regression for texture processing, BiSeNet for face segmentation, and BabylonJS for rendering. Runs entirely in browser with custom asset support.

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Writing

Teaching Machines to Notice

Jamnagar. Miles of pipe, thousands of workers, and cameras that never blink. Building real-time safety systems with DeepStream pipelines and graph neural networks.

Slow Paths, Fast Hands

What happens when you point a neural network at cricket footage with no labels. Generating training data from thin air, teaching SlowFast to see batting strokes, and the surprising gap between model accuracy and what actually matters.