Josue Flores's Profile PicColor mode icon

Josue
Flores

Software DeveloperSoftware DesignerSoftware Engineer

Learning to achieve &achieving to learn.

GitHub IconLinkedin Icon

Projects


Skills

checkmark icon

Java

checkmark icon

Python

checkmark icon

JavaScript

checkmark icon

TypeScript

checkmark icon

C++


checkmark icon

React

checkmark icon

MUI

checkmark icon

Django

checkmark icon

Flask

checkmark icon

Bootstrap 5

checkmark icon

Google React Charts

checkmark icon

Spring

checkmark icon

Spring Boot

checkmark icon

Express


checkmark icon

MySQL

checkmark icon

PostgreSQL

checkmark icon

REST APIs

checkmark icon

MongoDB

checkmark icon

Supabase

checkmark icon

Firebase


checkmark icon

Agile/Scrum

checkmark icon

Waterfall

checkmark icon

OOD

checkmark icon

SOLID

checkmark icon

SOA

checkmark icon

Microservices

checkmark icon

GoF Design Patterns


checkmark icon

HTML5

checkmark icon

CSS3

checkmark icon

Git/GitHub

checkmark icon

OpenGL

checkmark icon

CI/CD

checkmark icon

Docker

checkmark icon

Kubernetes

checkmark icon

Jira

checkmark icon

AWS

checkmark icon

Azure

checkmark icon

Vite

checkmark icon

JUnit 5

checkmark icon

Jest

checkmark icon

Node.js

checkmark icon

Linux

checkmark icon

Datadog

Experiences

CodePath logo
  • Mentored 180+ students in advanced Data Structures & Algorithms (DSA), guiding them through LeetCode-style problems to sharpen both their technical and behavioral interview skills
  • Hosted weekly office hours to deconstruct complex DSA concepts, fostering robust problem-solving methodologies for several algorithmic patterns
  • Tech Stack: Leetcode, VSCode, Replit, Slack, Zoom
AT&T Logo
  • Developed a Spring REST API service to enhance customer personalization for a 13M+ user base by processing real-time customer-based GUID events from Azure Service Bus
  • Enabled product-driven Exploratory Data Analysis by persisting event-driven user data into MongoDB, establishing a reliable source for enrollment trends and user behavior
  • Decreased MongoDB query latency by 89% for customer-facing microservices by engineering a consolidation service that unifies disparate customer data streams into a concise profile that updates at a specified interval
  • Built and trained an XGBoost/HistGradient ML model with 97% accuracy to identify and mitigate cybersecurity threats as part of a network micro-segmentation proof-of-concept
  • Tech Stack: Java, Azure, Spring Boot, MongoDB, Hoppscotch, Python, Flask, React, Docker, Kubernetes, CI/CD
MoneyLion logo
  • Automated the generation of 25K+ video assets by engineering a multithreaded Java Spring REST API, drastically reducing manual content creation efforts
  • Ensured service reliability by achieving 80% code coverage through substantial JUnit 5 unit and integration tests
  • Eliminated 1-2 weeks of recurring work by creating a Spring service to automate content tag assignment for 25K+ assets
  • Simplified the content moderation workflow by 25% by integrating an OpenAI-powered sentiment analysis service for over 180,000 user comments
  • Implemented Datadog alerts to monitor API and service performance relating to P95 latency, request calls, and request errors, generating a 4% faster issue response time for the Discover team’s Comment and Notification APIs
  • Tech Stack: Java, Spring, Spring Boot, SOA, OpenAI, Contentful, AWS DocumentDB, MongoDB, JUnit 5, Datadog, Kafka, Lombok
ConEdison logo
  • Generated a ~3% increase in company workflow by engaging in the acquisition of IT-related software/hardware equipment such as (Adobe Acrobat, Microsoft Visio, Microsoft Project) for 75+ internal/external customers
  • Facilitated the analytics process and IT operations of O&R as measured by monitoring the deployment status of active/inactive product licenses and the fulfillment of 45+ unresolved tickets within the End User Services department
  • Tech Stack: Oracle and Microsoft Excel
NSF logo
  • Constructed, trained, and evaluated 5+ distinct Convolutional Neural Network (CNN) architectures to perform supervised image classification
  • Assessed model robustness by subjecting CNNs to adversarial attacks (FGSM, BIM) and analyzing the resulting impact on classification accuracy and confidence scores
  • Tech Stack: Python, TensorFlow, Matplotlib, Numpy, Pandas, Google Colab

Education

CUNY - The City College of New York

B.E. Computer Engineering

Graduation Date: June 2022

NYU Tandon School of Engineering

M.S. Computer Science

Graduation Date: May 2026

Let's Talk