Machine Learning M A

mauricethefirst.com *******@***************.*** 305-***-****

Maurice Sanders

A I E n g i n e e r M a c h i n e L e a r n i n g E n t h u s i a s t A I T r o n s f o r m a t i v e L e a d e r S o f t w a r e A u t o m a t i o n D e v e l o p e r Summary

Software engineer and QA specialist pursuing advanced AI/ML education at Georgia Tech. Seeking to leverage my software development and automation skills as a springboard into AI and machine learning roles. Demonstrated ability to quickly learn new technologies and frameworks, with a keen interest in applying computational skills to AI-driven solutions.

Experience

Applied AI prompting techniques to develop automated testing workflows, demonstrating practical experience with machine learning tools and reducing manual intervention by 40%.

Implemented behavior-driven testing frameworks, creating 50+ feature files that showcase ability to translate complex software requirements into structured, data-driven approaches.

Developed automation scripts across Python, Java, and JavaScript, highlighting programming versatility and foundational skills relevant to machine learning and data science projects.

Collaborated with cross-functional teams to solve complex technical challenges, demonstrating the interdisciplinary communication skills crucial in AI/ML environments.

Systematically identified and resolved critical software issues, reflecting the analytical problem-solving mindset required in machine learning research and development.

Designed and maintained AWS Step Functions workflows for serverless applications, optimizing microservices architecture and operational efficiency.

Developed and tested serverless applications using AWS SAM framework, enhancing deployment processes and CI/CD pipeline integration. Conducted rigorous code reviews to ensure adherence to coding standards, best practices, and security guidelines. Collaborated with DevOps teams to automate testing and deployment workflows, improving system reliability and release speed. DevOps Quality Control Specialist February 2023 - present Comcast

Bellomy

August 2022 - November 2022

Projects

Northern Illinois University B.S. Computer Science DevOps Engineer

Georgia Tech University M.S. Ai/ML (May 2026)

Education

Skills

Technical Skills: Languages: Python, Java, JavaScript Test Automation: Selenium, Playwright, Cucumber, Visual Regression Testing Test Management: Jira, Test Planning, Defect Tracking AI Tools: OpenAI, Claude, Gemini, Llama 2

Cloud & DevOps: AWS (SAM, Step Functions) and Git

Emerging Interests: Financial Markets, Algorithmic Trading Quantitative Research

https://github.com/MrAfroTech/QuantResearch

This repository houses code and resources for quantitative research, primarily focused on financial markets and algorithmic trading. It contains scripts written in Python w/ these key functionalities: data analysis, backtesting, model development, signal generation, risk management:

Programming Language: Python 3.8+

NLP Library: Hugging Face Transformers (specifically the BART model) Data Format: JSON (for input data)

File Operations: Python's built-in file I/O for reading and writing files. Task Orchestration: NumPy, Pandas, SciPy, yfinance, pandas-datareader, TA-Lib, backtrader, Matplotlib, and Beautiful Soup Automated Visual Regression Testing

https://github.com/MrAfroTech/AutomatedVisualRegressionTesting This repository houses code and resources for ensuring pixel-perfect precision with automated visual regression testing projects. These initiatives focus on detecting UI changes, maintaining design consistency, and delivering flawless user experiences with speed and accuracy. Programming Language: JavaScript

Testing Framework: Playwright

Task Automation: Playwright's API for browser control and screenshot capture Image Comparison: Pixelmatch.

Automation

https://github.com/MrAfroTech/AutomatedVisualRegressionTesting This repository provides tools and scripts for automating desktop interactions. It focuses on tasks such as window management, application control, keyboard and mouse automation, and UI interaction, enabling users to automate repetitive tasks and improve productivity. Playwright

Sikuli: Image recognition-based GUI automation.

AppleScript: macOS task automation.

ChatBot Configuration

https://github.com/MrAfroTech/exDrinkBot

This repository contains the code for a full-stack chatbot application. The backend, built with Node.js and Express, handles API requests and interacts with the OpenAI API for natural language processing or a MongoDB database for data persistence. The frontend, developed using Java and React, provides a user-friendly interface for interacting with the chatbot. Key technologies and tools include: Backend: Node.js, Express.js

Frontend: Java, React

Natural Language Processing/Data: OpenAI API (for LLM functionality) or MongoDB (for database integration) Projects (continued)

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