Baja Llama Externship via Extern
I’m a Full-Stack Software Engineer and AI Engineer with experience in web development, backend systems, automation, QA testing, prompt engineering, and LLM evaluation. I work with tools like Python, J
🟢 Open to workA collection of projects that highlight my experience across software development, AI, machine learning, QA testing, and data-driven applications. Each project reflects my ability to turn ideas into f
Personal Project
Built a full-stack AI code review system using FastAPI and React. The application analyzes submitted code, applies weighted code-quality scoring, provides structured review feedback, and validates historical scoring data through CSV-based comparisons.
Personal Project
Built a machine learning project to predict road accident risk using Python, Pandas, and CatBoost. I prepared and cleaned the dataset, engineered relevant features, trained the prediction model, and evaluated its ability to estimate accident risk accurately.
Personal Project
Built a searchable QA case-tracking application using Flask and SQL. The system supports full CRUD functionality, allowing users to create, view, update, search, filter, and manage QA cases through a simple and organized interface.
I’m a Full-Stack Software Engineer and AI Engineer with experience in web development, backend systems, automation, QA testing, prompt engineering, and LLM evaluation. I work with tools like Python, J
I’m a technology professional who enjoys turning complex ideas into solutions that are useful, efficient, and easy to understand. My experience spans software engineering, artificial intelligence, data analysis, quality assurance, and technical problem-solving. I’ve worked on projects involving full-stack applications, AI model evaluation, machine learning, automated testing, APIs, and data-driven systems. I’m naturally curious, detail-oriented, and always interested in learning new technologies while continuing to strengthen my technical skills. I enjoy work that challenges me to think.
Externships
Baja Llama Content Creation and Influencer Strategy Externship
Baja Llama
Experience
Computer Science Expert
Handshake AI · Jun 2025-Present
AI Trainer and LLM Evaluator
Mercor · Oct 2018-Present
Generative AI Engineer
Randstad Inc · Jan 2023-Mar 2025
Software Engineer
Sysintel Inc · Jan 2016-Dec 2022
Education
Full Sail University
Bachelor of Science in Computer Science, Minor in Data Science
Herzing University
Bachelor of Science in Human and Health Services, Minor in Statistics
Skills
Personal Project
Built a full-stack AI code review system using FastAPI and React. The application analyzes submitted code, applies weighted code-quality scoring, provides structured review feedback, and validates historical scoring data through CSV-based comparisons.
Built a full-stack AI code review system using FastAPI and React. The application analyzes submitted code, applies weighted code-quality scoring, provides structured review feedback, and validates historical scoring data through CSV-based comparisons.
Developed the REST API, React interface, scoring logic, CSV validation workflow, and automated test suite. Created weighted scoring across multiple code-quality factors and used Pytest to verify API behavior, scoring calculations, and validation accuracy.
Successfully verified that the scoring system could distinguish between different levels of code quality. Clean, well-structured code achieved a 10.0 score, while demonstration code scored 7.6, confirming that the weighted review logic behaved as intended.
Personal Project
Built a machine learning project to predict road accident risk using Python, Pandas, and CatBoost. I prepared and cleaned the dataset, engineered relevant features, trained the prediction model, and evaluated its ability to estimate accident risk accurately.
Built a machine learning project to predict road accident risk using Python, Pandas, and CatBoost. I prepared and cleaned the dataset, engineered relevant features, trained the prediction model, and evaluated its ability to estimate accident risk accurately.
Prepared and transformed raw accident data for modeling, performed feature engineering, trained a CatBoost regression model, and validated model performance using evaluation metrics. I also analyzed feature importance to better understand which factors contributed most to predicted accident risk.
The final CatBoost model achieved an RMSE of approximately 0.0565, demonstrating strong predictive performance on the validation data. The project showed how machine learning can be used to identify risk patterns and turn transportation data into useful safety insights.
Personal Project
Built a searchable QA case-tracking application using Flask and SQL. The system supports full CRUD functionality, allowing users to create, view, update, search, filter, and manage QA cases through a simple and organized interface.
Built a searchable QA case-tracking application using Flask and SQL. The system supports full CRUD functionality, allowing users to create, view, update, search, filter, and manage QA cases through a simple and organized interface.
Developed the backend logic, database workflows, search and filtering features, and case management functionality. I also created automated tests with Pytest to validate core workflows such as creating, updating, searching, and deleting QA cases.
Delivered a functional QA tracking system that made test cases easier to organize, search, and manage. Automated testing helped confirm that the main CRUD workflows worked reliably and reduced the risk of regressions as features were added.