Opensource ML / AI @ Internet Scale at NVIDIA
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Accelerating data workflows at internet scale for foundational model training at NVIDIA. Previously architected ML platforms at Block and Iterable. MSE in Computer Science with a focus on Machine Learning from Johns Hopkins University
The Johns Hopkins University
Masters of Science in Engineering, Computer Science
January 1, 2017 – January 1, 2019
Shaheed Sukhdev College Of Business Studies
Bachelor of Technology (BTech), Computer Science
January 1, 2013 – January 1, 2017
St. Columba's School
Physics, Chemistry, Maths and Computer Science
January 1, 2007 – January 1, 2013
NVIDIA
Senior Software Engineer
August 1, 2024 – Present
San Francisco Bay Area
Square
Machine Learning Engineer
February 1, 2023 – August 1, 2024
San Francisco, California, United States · Hybrid
Iterable
Staff Machine Learning Engineer
May 1, 2022 – February 1, 2023
Iterable
Senior Machine Learning Engineer
May 1, 2020 – May 1, 2022
Iterable
Machine Learning Engineer
February 1, 2019 – May 1, 2020
The Johns Hopkins University
Graduate Research Assistant
September 1, 2018 – December 1, 2018
The Johns Hopkins University
Machine Learning Researcher
August 1, 2018 – February 1, 2019
Goldman Sachs
Summer Technology Analyst
May 1, 2018 – August 1, 2018
Greater New York City Area
The Johns Hopkins University
Course assistant for Machine Learning
January 1, 2018 – May 1, 2018
The Johns Hopkins University
Machine Learning Research Assistant
December 1, 2017 – May 1, 2018
TATA Power
Machine Learning Intern
January 1, 2017 – June 1, 2017
New Delhi Area, India
Octo.ai
Data Engineering Intern
June 1, 2016 – August 1, 2016
Harley-Davidson India
Market Research Intern
August 1, 2015 – September 1, 2015
Zostel
Software Developer Internship
June 1, 2015 – July 1, 2015
Social Cops
Software Engineering Intern
May 1, 2014 – January 1, 2015
WYSIWYG Conference
Associate
January 1, 2013 – January 1, 2014
MedTrove
Co-Founder
October 1, 2012 – December 1, 2014
Exploring different techniques in Visual Question Answering
April 1, 2018 – May 1, 2018
We experiment with various methods and reproduce them in PyTorch. We try to analyse the different models presented and also our own model which uses attention. In totality we experiment with 7 different models, in a constrained environment of training upto only 10 epochs. We explain the models we tried, and the choices we made while creating our own model. We additionaly release an extremely lightweight yet modular code which can be used to perform more experiments with no time setting up the framework.
Parallel Implementation of Adaboost with OpenMP
April 1, 2018 – May 1, 2018
We develop a parallel AdaBoost algorithm that exploits the multiple cores in a CPU via light weight threads using OpenMP. We propose different algorithms for different types of datasets and machines, achieving upto 22x Speedup on 32 cores.
Comparison of different Dimensionaly Reduction algorithms on ASL dataset
March 1, 2018 – April 1, 2018
Exploring the latent dimension space of the American Sign Language dataset from different techniques such as PCA, PPCA, Isomap, VAE etc.
Action Recognition in Videos using RNN
November 1, 2017 – December 1, 2017
Used Resnet18 to extract features from frames for spatial data, and passed the sequence to a GRU Recurrent Neural Network.
Doodle Classification using 7 layer CNN
November 1, 2017 – December 1, 2017
Achieved ~97% accuracy on a subset of data. (only 5 classes). Project for Machine Learning Class.
Local Content Based Image Retrieval Application
April 1, 2017 – Present
In this project, I was focussing on setting up a local image search engine which will search an image based on it's content rather than the tags associated with it. With the help of OpenCV and Tesseract I was able to extract readable textual content from images and later store them to a database. With the help of a Flask powered frontend one could query these images for the text within them.
Feature Based Opinion Mining
November 1, 2016 – Present
Used NLP to extract opinions in customer reviews. The opinion miner did not extract the overall sentiment of the entire review rather, what the customer liked or did not like as mentioned in the review. It would treat each sentence containing a distinct feature as a separate review.
Light Sensing Robot using Differential Drive Algorithm
January 1, 2016 – Present
Used Arduino Uno, a L293D to drive DC motors and Photoresistors to steer it in the direction of brighter area.
NodeJS Client Ticketing System using WebSockets
January 1, 2015 – Present
Developed a "support staff and client" ticketing portal using NodeJS to make a websocket server for real time communication to resolve issues on real time and took consideration of clients feedback.
Web Development Projects
January 1, 2013 – January 1, 2015
Developed custom Content Management Systems (both frontend + backend) as per the need of the client. The portfolio includes : - The 72 Hour Project - Singapore Angel Networks - SRCC Grievance Portal - Global Conferences - Encore Sourcing Asia Ltd - Benches Now and Then.
IUV.be OpenSource URL Shortener
October 1, 2011 – Present
An opensource URl shortener Features - Ability to ban spam users - Monetise redirection page and index page by adding advertisements through admin panel - JSON + TXT + XML + Plain Text API with sample code. - Viewing Stats - Easy to Install. Comes with Installation file
iLike
January 1, 2010 – Present
A facebook app which went viral grabbing 60,000+ page impressions a day and reached alexa ranking of 23,000 at it's peak.
Basic Mountaineering Course
Atal Bihari Vajpayee Institute of Mountaineering and Allied Sports
June 24, 2026 – Present
Designing State of the Art Recommender Systems
Sphere
June 24, 2026 – Present
Causal Inference
Coursera
June 24, 2026 – Present
Cultural Fit Analysis
The candidate's extensive experience in various companies, including startups (Zostel, Social Cops, MedTrove) and large corporations (NVIDIA, Square, Iterable, Goldman Sachs, TATA Power), demonstrates adaptability to different organizational cultures. The diverse personal projects, ranging from robotics to web development and advanced AI, indicate a strong drive for learning and innovation, which aligns well with dynamic, growth-oriented environments. The target role of 'Data Analyst' is a good fit given the strong background in data science, machine learning, and data engineering, although the candidate's experience leans more towards ML Engineering, suggesting potential for growth into more advanced analytical roles.
Soft Skills & Operational Fit
The candidate's project descriptions and work history suggest a proactive and innovative individual, capable of taking initiative (e.g., co-founding MedTrove, leading architecture decisions at Social Cops). The diverse range of projects, from web development to advanced ML research, indicates adaptability and a broad technical curiosity. The experience as a Course Assistant also points to communication and mentorship abilities. However, without specific psychometric test results, a detailed assessment of stress handling, work attitude, and team collaboration is not possible.