I'm an aspiring machine learning engineer focused on building AI systems that work for people who are usually left out of the default design: patients who don't speak "standard" English, first-generation students, communities underrepresented in the datasets models are trained on. I care about the gap between a model that performs well on paper and one that's actually reliable for the people it's supposed to serve.
My work spans real-time systems engineering, applied ML research, and full-stack development. I've trained classifiers on tens of millions of records, built agent-based AI systems from scratch, and led a research study that directly changed how a computing program supports its students.
Right now: Software Engineering intern at Lockheed Martin (RMS), building a decentralized multi-agent system in Unreal Engine, while volunteering as a STEM educator at the Emerald Coast Science Center and serving as a CUNY Fellow with ALPFA. I completed the Break Through Tech AI Fellowship at Cornell Tech in April 2026, a year-long program spanning two industry-partnered studio projects.
- RAG-based medical intake assistant that interprets dialectal inputs (AAVE, Spanglish) that standard intake systems fail to parse
- Led a 3-person team from concept to working demo in an 11-day build cycle
- Tech: React, Python, RAG, ChromaDB, OpenAI API
- View Project
Built during the Break Through Tech AI Studio (Cornell Tech)
- Adaptive reading assistant for neurodivergent students, built on a LangGraph agentic state machine with FAISS vector retrieval
- Dual-parser PDF routing (pdfplumber/LlamaParse) for real-time interventions via FastAPI/React
- Tech: LangGraph, FAISS, FastAPI, React
- View Project
- Applied k-means clustering, gradient boosting, and SHAP analysis to a 149K-record longitudinal student dataset
- Uncovered a 3.9x disparity in first-generation representation between struggling and high-achieving students, and an 18-point gender-specific attrition gap: findings that directly shaped BMCC's Women in Computing programming
- Tech: Python, pandas, scikit-learn, SHAP
- Research with Prof. Mohammad Azhar
- View Project
- Centralized job platform simplifying on-campus job access for international students, cutting HR processing time 50%
- Led a 4-person team through a single-day build cycle
- Tech: JavaScript, Node.js, MongoDB
- View Project
Production Deployment: Blackstone Sprinternship, January 2025
- Enterprise analytics dashboard on Splunk Cloud, AWS Lambda, and Snowflake tracking 12+ deal KPIs
- Cut stakeholder time-to-insight 40%, delivered within a 4-week sprint as 1 of 5 interns selected for the BXTI team
- Tech: Splunk SPL, Snowflake, AWS Lambda
Native C++/Qt6 application, built from scratch
- Full-stack marketplace for academic materials with a four-table relational schema (SQLite via Qt SQL) and a course-aware recommendation engine
- Session-based auth (SHA-256 hashing, UUID tokens), filterable/paginated catalog, custom UI with Qt's animation framework
- Tech: C++, Qt6, SQLite, CMake
- View Project
Languages:
AI & Machine Learning:
scikit-learn Keras/TensorFlow LangGraph FAISS RAG ChromaDB SHAP k-means gradient boosting prompt engineering
Development:
Cloud & Tools:
· Snowflake · Splunk Cloud (SPL) · Jira
Databases:
· SQL
- Advanced deep learning architectures and MLOps/deployment practices (model monitoring, concept drift, A/B testing)
- Real-time multi-agent systems in Unreal Engine (Gameplay Ability System)
- Contributing to open-source ML tooling
- Machine Learning Foundations Certificate: Cornell University (Summer 2025)
- Break Through Tech AI Fellow: Cornell Tech (Aug 2025 to Apr 2026, completed)
- ALPFA CUNY Fellow: Association of Latino Professionals For America (2025)
- ACM Europe Summer School on Data Science: Ioannina, Greece (selective international program, 2025)
- C++ Templates and STL / C++ Best Practices for Developers: LinkedIn Learning (Dec 2024)
- Mental Health First Aid USA: National Council for Mental Wellbeing (2024-2027)
- President, Women in Computing (ACM-W) @ BMCC (Sept 2024 to May 2025): Led a 22-member chapter, driving 85% member retention and a 65% rise in event participation; organized FAANG recruiter panels and hands-on technical workshops
- Break Through Tech AI Fellow (Aug 2025 to Apr 2026, completed): Year-long ML fellowship spanning two industry-partnered studio projects (Cadence Design Systems, Agentic AI)
- CUNY Fellow, ALPFA (Apr 2025 to present): Ongoing fellowship with the Association of Latino Professionals For America, providing professional development and leadership training
- Member, Rewriting the Code (Mar 2024 to present): Active in a national women-in-technology community offering mentorship, networking, and career development resources
- Research Lead: Quantitative research on institutional retention gaps for underrepresented students in computing
Seeking Machine Learning Engineering roles where I can:
- Build AI systems that work reliably for users who aren't the default assumption
- Apply predictive modeling to problems with real institutional or clinical stakes
- Keep learning in public, through research, hackathons, and shipped code
- Mentor other underrepresented technologists coming up behind me