Varun Rawal

Varun Rawal

SDE 2 · Amazon Ads | MS ML, CMU | Software & AI/ML Engineer

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Pages

Posts

Future Blog Post

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Blog Post number 1

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academic_qualifications

Carnegie Mellon University

CMU Pittsburgh Campus

Master of Science in Machine Learning, Aug 2019 - Dec 2020

Machine Learning Department, School of Computer Science

awards

SAIL Proficiency Award 2012-13

Published:

Awarded Certificate of Merit-cum-Cash Award by Education Department, Bhilai Steel Plant, Steel Authority of India Limited, for Outstanding Proficiency in All India Entrance Examination for Professional Course in Engineering 2012-13

B.P. PODDAR SCHOLARSHIP RECIPIENT 2015-16

Published:

Granted Scholarship of INR 1000 per month awarded to the best students of the final year class of B.Tech. (Hons.) securing the highest CGPA at the end of the VI or VIII semesters.

GORA LAL SYNGAL MEMORIAL SCHOLARSHIP RECIPIENT 2015-16

Published:

Granted Scholarship of INR 2500 per month, awarded to the second highest CGPA holder clearing all prescribed requirements of curriculum and having no backlog after 6th semester amongst the 4-year B.Tech. (Hons.) CS / EE /EC Students.

experiences

experiences_acad

Carnegie Mellon University Permalink

Research Assistant

Sep 2020 - December 2020

Supervisor : Prof. Beibei Li , Pittsburgh, PA, USA

  • Responsible for development and maintenance of an Android/iOS research application platform.

experiences_industry

Adobe Systems Permalink

Senior Software Development Engineer (SDE II) — Adobe Experience Cloud

Jun 2017 – Dec 2018

Adobe Experience Cloud, Noida, India

  • Architected and built full-stack solutions for Adobe Experience Manager (AEM) Interactive Communication applications, designing data integration services and document fragment-based systems to support scalable, cloud-based business process automation
  • Worked on independent project for Intelligent Chatbot services using NLP for query-based interaction on personalized customer contexts derived from statement reports

Adobe Systems Permalink

Senior Software Development Engineer (SDE II) — Adobe Creative Cloud

Jan 2019 – Aug 2019

Adobe Creative Cloud, Noida, India

  • Developed core components of a vector graphics editing application for iPad, implementing advanced Pen, Direct Selection, and Snapping tools — enabling precise design workflows and smooth transition of desktop-grade capabilities to mobile platforms
  • Worked intensively in C++ and iOS platforms on Adobe Illustrator for iPad (Project Proteus)

Microsoft USA Permalink

Software Engineer 2

May 2021 – Jul 2023

Microsoft, Bellevue, WA

  • Spearheaded telemetry and dashboard development for Office Excel Charting, revolutionizing data visualization and analysis processes; architected comprehensive telemetry dashboards and optimized data querying mechanisms
  • Led implementation of Network Security Groups on Private Link Connections using SDN Appliance Middlebox on Azure, enhancing network security and performance

CeraMD.ai Permalink

Chief Technical Officer

Sep 2023 – Dec 2023

CeraMD.ai, Boston, MA

  • Designed and implemented a comprehensive AI-driven medical care system, integrating chat services, web crawlers, and advanced NLP models
  • Spearheaded development of a retriever-based (RAG) system utilizing OpenAI and LLaMA models, enabling real-time evidence-based medical insights
  • Orchestrated cloud architecture on AWS, implementing microservices, serverless functions, and efficient data pipelines for scalable AI operations

HyperWater.ai Permalink

Consultant & Technical Lead

Jan 2024 – Nov 2024

HyperWater.ai, Dallas, TX

  • Architected and implemented an advanced ITB Preferences module leveraging LLMs and rule engines to automate decision-making processes for subcontractors
  • Engineered a scalable system integrating LLMs with Drools for converting user preferences into structured decision flows, enhancing efficiency in document processing
  • Built agent-based systems to automate ITB document processing, applying OCR tools for extraction and passing through LLM-generated decision flows

Zaytun AI (formerly LIVEr) Permalink

Senior Backend Engineer (Contract)

Dec 2024 – Mar 2025

Zaytun AI, San Jose, CA

  • Built a vector search-based recommendation system leveraging LLM embeddings to match users with personalized short-form food video content and local restaurants, supporting a TikTok-style platform
  • Migrated from Vertex AI Vector Search to Qdrant, reducing infrastructure costs and improving deployment flexibility
  • Designed and deployed backend services on Firebase and Google Cloud, including authentication, real-time data sync, and push notifications for iOS launch

Amazon Permalink

SDE 2 — Amazon Ads

Mar 2025 – Present

Amazon Ads, Seattle, WA

  • Designed and delivered multiple end-to-end features across API models, backend services, website backend, React frontend, and CDK infrastructure, contributing to ~18 packages in the Ads Permission Delegation Platform
  • Architected and implemented batch ADD/DELETE APIs with detailed error handling, region validation, and CloudWatch-backed status metrics; refactored policy configuration for always-on policy-based access control
  • Built dependency service monitoring across accessor layers with CloudWatch dashboards and alarms, improving observability and incident response; resolved Sev-2 issues and mitigated dependency confusion vulnerabilities
  • Built a micro-frontend KPI visualization widget from scratch using React and Webpack Module Federation, including CDN asset delivery, i18n support, and CDK-based deployment pipelines
  • Authored 75+ production code reviews and reviewed 140+ peer changes across backend, frontend, and infrastructure

experiences_intern

IBM India Research Laboratory (IRL) Permalink

Research Intern (UG Summer Training)

May 2015 - June 2015

Supervisor : Dr. Sameep Mehta, Senior Researcher & Manager, IBM, New Delhi, India

  • Actively participated in and contributed to the partial fulfilment of the Project \Construction of Knowledge Graph and Use of Semantic Knowledge Graph in Supervised Training and Blended Learning”
  • Prepared a model for Knowledge Graph construction by discovering relations and establishing links between graph nodes, and completed implementation in JAVA, collecting 4000 records by crawling a Research Repository as the work dataset.
  • Applied a variety of text-mining techniques like Entity-Extraction, Part-of-Speech Tagging and Similarity Detection using Online JAVA Services and JAVA libraries. Finally demonstrated a 3D visualization of the growing Knowledge Graph using visualization Library tools

Adobe Big Data Experience Lab (BEL) Permalink

Research Intern (B.Tech. Summer Training)

May 2016 - July 2016

Supervisor : Harvineet Singh, MTS, Adobe Research Labs, Adobe Research Bangalore, India

  • Actively participated in and contributed to the fulfilment of the Project based on \Analytics of Multi-Channel Customer Data”
  • Applied Machine Learning models to predict customer affinity to interact in a given channel with limited information, given this information of interaction across other channels.
  • Designed a unique and novel solution approach exploiting CCA (Canonical Correlation Analysis) for suggesting ways for predicting customers’ purchase behavior using a shared feature space which captures cross channel correlations instead of directly merging the input channels’ data or predicting on the basis of single channel.

Qeexo Co. Permalink

ML Research Intern (Master's Summer Training)

June, 2020 - Aug, 2020

Supervisor : Dr. Rajen Bhatt, Pittsburgh, PA, USA

  • Worked on off-device and on-device Real-Time Clustering & Visualization on Sensor data for Machine Learning platform AutoML - in development for execution of ML libraries on Sensor-Data for Embedded devices like Arduino Sensorboard, etc.

portfolio

publications

Supporting Throughput Fairness in IEEE 802.11ac Dynamic Bandwidth Channel Access: A Hybrid Approach

Published in IEEE Conference 2017, 2017

Paper accepted at 42nd IEEE Conference on Local Computer Networks (LCN). 2017. for publication in its proceedings.

Recommended citation: R. Karmakar, V. Rawal, P. K. Bishoyi, S. Chattopadhyay and S. Chakraborty, "Supporting Throughput Fairness in IEEE 802.11ac Dynamic Bandwidth Channel Access: A Hybrid Approach," 2017 IEEE 42nd Conference on Local Computer Networks (LCN), Singapore, 2017, pp. 462-470, doi: 10.1109/LCN.2017.93. https://www.researchgate.net/publication/321122477_Supporting_Throughput_Fairness_in_IEEE_80211ac_Dynamic_Bandwidth_Channel_Access_A_Hybrid_Approach/link/5b8ed7fb92851c6b7ebffb7a/download

talks