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Agentic AI @ Google
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Building distributed systems at Google for Cloud AI offerings. In the past, I've helped build the industry’s first AI tool for chip design (DSO.ai) at Synopsys. I have a strong background and over four years of experience in Machine Learning Infrastructure, Systems and Software Development for AI applications.
Birla Institute of Technology and Science, Pilani
B.E. (Honours), Electronics and Communication Engineering
N/A – Present
UCLA
MS, Electrical and Computer Engineering
N/A – Present
Software Engineer
June 1, 2025 – Present
San Francisco Bay Area
Synopsys Inc
Staff Engineer, Machine Learning
October 1, 2023 – July 1, 2025
San Francisco Bay Area
Synopsys Inc
Software Engineer II
November 1, 2021 – September 1, 2023
San Francisco Bay Area
MathWorks
Software Engineer
April 1, 2021 – November 1, 2021
Boston, Massachusetts, United States
MathWorks
Software Engineer Intern
September 1, 2020 – December 1, 2020
Boston, Massachusetts, United States
Synopsys Inc
Machine Learning Intern
June 1, 2020 – September 1, 2020
Mountain View, California, United States
University of California, Los Angeles
Graduate Teaching Associate
April 1, 2020 – September 1, 2020
University of California, Los Angeles
Graduate Teaching Assistant
January 1, 2020 – March 1, 2020
University of California, Los Angeles
Graduate Teaching Assistant
September 1, 2019 – December 1, 2019
Qualcomm
Software Engineering Intern
January 1, 2019 – June 1, 2019
Hyderabad Area, India
EY
Software Engineering Intern
May 1, 2018 – July 1, 2018
Hyderabad Area, India
Tata Communications
Software Engineering Intern
May 1, 2017 – July 1, 2017
Pune Area, India
Mytrah Energy
Software Engineering Intern
January 1, 2017 – August 1, 2017
Hyderabad Area, India
Fake News Detection
August 1, 2018 – December 1, 2018
Worked with Nikhil Madaan and Prof. Aruna Malapati on 'Fake News Detection using Deep Learning Techniques'. To solve the problem of filtering out illegitimate news articles, we proposed a novel Deep Learning technique by working on a dataset comprising 9,400,000 labelled news articles. By using properties of Natural Language, we extracted certain readability and linguistic features, and substantially improved upon our accuracies. Our analysis consists of the performance of six classification algorithms, thereby suggesting the best algorithm for detecting fake news.
Visible Light Communication in Vehicular Ad-Hoc Networks
August 1, 2018 – December 1, 2018
Worked with Prof. Sudeepta Mishra to build a tool in C++ to simulate 'Visible Light Communication in Vehicular Ad-Hoc Networks'. Designed the simulator using the VLC module of the 'ns3' (Network Simulator 3) library in C++ and integrated it with Open Street Maps and SUMO (Simulation of Urban Mobility) to determine efficient resource allocation in tunnels (absence of visible sun-light).
Sun-Tracking Solar Panel
January 1, 2017 – April 1, 2017
An Internet of Things (IoT) based project which involves the development of a working-prototype of a solar panel which tracks the sun throughout the day in order to maximize the amount of sunlight intensity for absorption.
AWS Fundamentals: Going Cloud-Native
Amazon Web Services (AWS)
June 28, 2026 – Present
Sequence Models
Coursera
June 28, 2026 – Present
Level 5 Piano
Trinity College London
June 28, 2026 – Present
AWS Fundamentals: Building Serverless Applications
Amazon Web Services (AWS)
June 28, 2026 – Present
AWS Fundamentals: Addressing Security Risk
Amazon Web Services (AWS)
June 28, 2026 – Present
Convolutional Neural Networks
Coursera
June 28, 2026 – Present
Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization
Coursera
June 28, 2026 – Present
Neural Networks and Deep Learning
Coursera
June 28, 2026 – Present
AWS Fundamentals: Migrating to the Cloud
Amazon Web Services (AWS)
June 28, 2026 – Present
Natural Language Processing in TensorFlow
Coursera
June 28, 2026 – Present
Deep Learning Specialization
DeepLearning.AI
June 28, 2026 – Present
Structuring Machine Learning Projects
Coursera
June 28, 2026 – Present
Cultural Fit Analysis
The candidate's project diversity, ranging from deep learning to IoT and network simulation, shows a broad interest and adaptability. However, the target role is 'Data Analyst', while the candidate's experience is heavily skewed towards Software Engineering and Machine Learning Engineering. While there are data analysis components in past roles (e.g., EY internship with R integration, 'Fake News Detection' analysis), the core experience is not directly aligned with a dedicated Data Analyst role, which might require a stronger focus on statistical analysis, data visualization, and business intelligence tools. The certifications in Deep Learning and AWS are valuable but do not directly address core data analyst skills.
Soft Skills & Operational Fit
The candidate's resume indicates experience in collaborative environments (e.g., working with professors, team projects) and teaching roles, suggesting good communication and teamwork skills. The descriptions of projects and roles are clear and professional, indicating strong operational fit.