Google

Software Engineer (July 2022 - Present)

• Built Cloud infrastructure to onboard new acquisitions and expand internal use of GCP
• Automated deployment configuration to simplify region & zone changes using C++ for international users
• Engineered solution in a cross-functional team to evaluate current product gaps in GCP
• Collaborated with external teams to deploy incremental infrastructure updates
• Expanded integration tests and increased internal test coverage by 20%
• Designed a product demo for stakeholders and created materials to educate internal teams
• Reduced RPC service latency to meet product requirements

Technologies: C/C++, GCP, Google related tools

Zebra Technologies

Software Engineering Intern (May 2020 - Aug 2021)

• Reduced manual overhead by writing server-less functions in GCP to automate and notify server of changes
• Removed the need of a technician by implementing over-the-air updates for deploying features in Rust
• Created and patched Flask endpoints in Python to concurrently communicate with multiple robots over a frontend UI
• Maintained realtime communication with server and other sub-systems of the robot in Rust and C++
• Migrated to PostgreSQL DB from SQLite to improve concurrency and simplify migrations between versions
• Expanded Python and Rust test coverage by 50% to not deviate from intended design using CI pipeline
• Supported remotely as on-call engineer while Proof of Concept testing took place in Germany

Technologies: Python, Rust, C/C++, SQL, GCP

Humans of Skule

President, WebMaster (May 2020 - April 2022)

• Leading a group of 15 students to interview students & share their experiences with 13k+ online audience
• Developed archive website in React with an automated gallery system to display latest photos

Technologies: HTML/CSS, React

Web Developer

Volunteer (Oct 2020 - Aug 2021)

Collaborated with Senior Engineer to implement web design spec in React under 2 months

Technologies: HTML/CSS, React

Physics based indoor localization using Machine Learning (Sep 2021 - May 2022)

• Built a dataset containing received signal strength indicator from 5 transmitters over 2600+ receiver locations
• Implemented ANN, KNN and Random Forest to receive a 70% success rate in determining location of a user

Technologies: Python

Python Libraries: Python, Numpy, Scikit

Pet Adoption Prediction

• Leveraged Google Vision to process 60,000 images and NLP API to analyze text for dataset cleanup
• Trained a custom 4-layer AlexNet CNN and a 5-layer ANN to separaelty analyze the data
• Joint trained both nerural networks to predict the adoption rate of a pet with an accuracy of 69.11%

Technologies: Python

Python Libraries: Pytorch, numpy and pandas

Image Processing and Sentimental Analysis: Google Vision API and NLP

Maps Project

Created a functional map of 12 cities. Map had the ability to find the shortest distance between two intersections, find closest hospital and police station and an interactive UI.

Final proposal for the project was to be used by Uber for ensuring safety of passengers.

Technologies: C++ and Glade for UI

Crossword

Created a crossword game which is projected using VGA. The user uses the keys 1 and 2 on the FPGA to move to specific position in the game and key 4 to submit the answer.

Technologies: C and Assembly