Los Angeles Metropolitan Area
Field Engineer for Amazon Dash Carts New Product Introduction Operations team. Launched successful deployment of the Dash Cart in Amazon Fresh stores throughout the US. Responsibilities included Identifying, ticketing, and troubleshooting HW/SW failures. Creating Standard Operating Procedures, Data Collection, Data Analysis, conducting UX user research, creating Process Map Visuals, UI design wireframes and more!
API created for Back-end Web Development class, includes four micro-services called User, Tracks, Playlist, and Descriptions that make their respective API calls. This project was coded in Python and went through three iterations, for the first part I was dev-ops and I was responsible for setting up the database and creating automated Tavern testing files. For the second part I was responsible for scaling our web application, for this I had to implement sharding on the tracks database table and update the Tracks microservice respectively. For part 3 I was responsible for upgrading our project from using mysql to using a nosql database called Cassandra, this required me to refactor all 4 microservices and redesign our tables to remove normalization. This project was challenging yet very rewarding as I learned many new Back-end skills.
A community ranked recipe search app. The application is written in Kotlin and features Android Jetpack components such as ViewPager2 and Compose. Meal Pal obtains data from a REST APl using Retrofit, then fetches rank information from Firebase. Once the recipes and rank are received through an AsyncTask(now deprecated) the recipes are organized according to rank and the data is loaded to the user interface.
created a client server protocol for transferring any file.
Gym Pal is an Android application I began working on in 2017. Gym Pal is written in Java and uses many components from the now deprecated Android support libraries. The Application is available for download on the google play store.
I Fullerton is an Android application that is intended to be a forum for CSUF students.
Nutri Smart is an Android application that uses the camera sensor on android devices to detect food items and determine their nutritional values. For this project I used Googles Machine Learning kit to recognize food items and I used the USDA nutritional database to retrieve nutritional data.