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My focus in developing mobile apps for Apple products that utilizes AI, machine learning, AR/VR, APIs, libraries, bluetooth communications, and other technologies. As a software engineer, nothing makes me happier than creating features and products that positively impacts as much people as possible.
Adept on developing internal tools, scripts, REST APIs, Firebase services, AppleScript, automation, and a Data Science tasks

• Software Engineer 2 at in consumer automotive mobile application team in Chandler, AZ. Mostly worked on Garmin's apps like Drive, Tread, and Explore, however, other code I wrote and features implemented may have been added to other Garmin apps.

• Software Engineer at multiple small to medium size companies like Bolar, StrepScan, Multiverse, and ElevatedEra

• BS degree in Computer Science from Domincan University of California (2021) in Mobile Development and Data Science from at a San Francisco, CA campus

• Mobile Development Teacher's Assistant at

• Design and develop new features, fix bugs, refactor legacy code, wrote documentation, and collaborate across multiple teams, and mentored colleagues

• Utilized Djinni and C++ to create cross-platform APIs for iOS and Android applications

• Developed iOS apps using Swift, SwiftUI, and Objective-C that communicates with Garmin devices over Bluetooth Classic (BT), Bluetooth Low Energy (BLE), and Cross-Transport Key Derivation (CTKD)

• Created internal tools using Python, AppleScript, and bash to generate code for productivity

• Mentored new hires, showing best practices, company coding standards, Xcode’s various tools, debugging methods, Git, Jira, Gerrit, and ITStash workflow

• Greatly increase app download to user sign ups ratio by simplifying and debugging onboarding and authentication flow by using Firebase’s MLVision, Barcode Scanning, and Text Recognition for scanning texts and barcodes for the user’s driver license

• Improved security by using KeychainSwift for storing sensitive data into the keychain, SafariServices to show parts of the website on the iOS app, and applying best practices in Cloud Storage for files and Cloud Firestore as the database for storing data

• Increased retention rate and daily active users by implementing a chatting feature using UIKit, MessageKit, InputBarAccessoryView for its user interface, PhotoKit, AVKit, TLPhotoPicker for handling photos and videos, File System and Kingfisher for caching photos and videos, and Firebase’s Firestore and Storage as the backend for data synchronization

• Integrated Stripe for landlord reward system and paperless application’s payment

• Created Firebase Cloud Functions shared by the website, Android, and iOS in Node.js

• Implemented profile page

• Architected and designed backend and iOS app with a UML diagram

• Designed high quality mockup UI of the app using Figma and implemented in SwiftUI

• Utilized Firebase Firestore for real time audio synchronization for multiple users

• Implemented audio caching using Apple’s FileSystem and Kingfisher for image caching

• Implemented group audio chat using Agora

• Implemented most of the features which includes: user authentication, real-time audio player for multi users using SwiftUI and MVVM pattern

• Annotated and labeled 700+ throat images using IBM Cloud Annotations

• Managed JupyterNotebook and other Python packages using virtualenv in order to train and create the machine learning model

• Utilized Python’s json, csv, and os APIs to format annotations.json file IBM Cloud Annotations outputted into a .csv file and to a specific format TuriCreate requires to create, train, and export a YOLO machine learning model

• Draw bounding boxes using Apple’s AVFoundation to show live rear camera preview

• Load the model using Apple’s CoreML and Vision to detect each throat parts, labeling, and showing location to enable autofocus and auto-capture features to capture medically usable images

• Enhanced user experience by improving visual and audio feedbacks, providing instructions based on specific throat part size showing or missing

• As the PM, I gave clear instructions and deliverables to a team of 7 software engineers and 3 industry partners enabling smooth development and communication in meetings.

• As the lead engineer, I coached and pair programmed with other software engineers to debug or help foresee potential blockers and

• Developed the AI to detech throat parts and display it live in the iOS app by labeling images using IBM Cloud Annotations, trained and created a YOLO CNN model using TuriCreate library, using Apple's AVKit and MLKit to display a bounding box and the predicted label around the throat parts.

🎁 Projects	⭐ Stars	📚 Forks	🛎 Issues	📬 Pull requests
StringsUtility
UserAuth-Starter
SnailMail