Full Stack Developer · ML Engineer · Consultant
~$ cat passion.txt →
I'm a Computer Science student at California State University, Los Angeles, graduating in 2026. My work sits at the intersection of full stack development and machine learning — I love building intelligent systems that are both technically deep and user-facing.
As team lead for the Golden Eagle Flight Plan — an AI-powered university platform — I led 10 developers through Agile sprints, architected RESTful APIs, and presented directly to faculty and the Provost liaison.
Beyond code, I bring a strong consulting and sales mindset from years as a top-performing rep, where I consistently exceeded targets by 120–150%. I approach engineering problems the same way: understand the stakeholder, deliver measurable results.
Collaborating on AI research initiatives with top labs. Improving LLM performance across specialized domains through prompt engineering and systematic evaluation of model responses.
Top-performing sales rep consistently exceeding quota by 120–150%. Ranked among the highest performers company-wide. Trained and mentored new team members and managers on sales strategy and customer engagement.
Cross-platform AI-powered student success app for CSULA with JWT-based auth across 4 user roles. Architected 20+ RESTful endpoints backed by 6 MongoDB schemas, a 4-tier gamified progression system with 36 milestones, and a hashtag-driven personalization engine. Partnered with the Provost liaison and led a team of 10 developers through Agile sprints.
Face recognition system using Principal Component Analysis for dimensionality reduction and Support Vector Machines for classification. Demonstrates core ML pipeline skills: preprocessing, feature extraction, model training, and evaluation.
Kaggle competition entry predicting passenger transport outcomes. Built and compared Logistic Regression, Decision Tree, and Random Forest models. Performed feature engineering, hyperparameter tuning, and cross-validation optimization.
Advanced ML project predicting FIFA player market value with regression models. Diagnosed why Linear Regression, Decision Tree, and MLP all produced negative R² on the original Kaggle dataset, then validated the hypothesis on a real-world FIFA dataset — reaching R² 0.4552 and RMSE 4.25M EUR. Applied SelectKBest, PCA, Ridge/Lasso tuning, and 10-fold cross-validation throughout.
3D board game-style RPG built in Unity. Features turn-based mechanics, tile-triggered events, player health and gold systems, and modular architecture with StageManager and SoundManager systems using OOP and state management.
I'm actively looking for software engineering, ML, and consulting opportunities. Whether you have a role in mind, a project to collaborate on, or just want to connect — I'd love to hear from you.