Michael E. Marin

Mr. Cooper Group — Dallas, TX

• •Supported agentic AI products for customer service automation across Azure DevOps and MySQL.
• •Participated in product experimentation, user validation, and AI feature evaluation activities.
• •Collaborated with product, engineering, and business stakeholders on AI and machine learning initiatives.
• •Worked in a cross-functional environment translating business requirements into technical deliverables.

Personal Applied-AI / Retrieval Engineering Project

• •Built a production-style RAG platform with FastAPI, PostgreSQL/pgvector, Redis, asynchronous ingestion, hybrid retrieval, reranking, Prometheus metrics, and a React operations console.
• •Benchmarked BM25, all-MiniLM-L6-v2 dense retrieval, RRF, and a cross-encoder trained only on SciFact's disjoint training split across 5,183 documents and 300 held-out queries; RRF led with 0.8059 Recall@10 and 0.6816 nDCG@10.
• •Built reproducible evaluation and load-testing pipelines with versioned datasets, artifact checksums, per-query traces, and CI quality gates; recorded 24.56 ms p50 and 31.75 ms p95 over 9,234 successful requests to the local-provider stack.

github.com/xmike04/RAG_OPS · SciFact Benchmark Report · Load-Test Summary

NASA PACE · University of Maryland IMD · University of North Texas

• •Led a 5-person team building a real-time computer vision and interactive visualization system for NASA PACE satellite data.
• •Developed gesture-recognition and multi-camera tracking workflows using OpenCV, CUDA, Unity, and ZED stereo cameras.
• •Built interactive data visualizations for real-time oceanographic satellite analytics.
• •Contributed to deployment automation and technical infrastructure for the exhibit.
• •The WAVE installation premiered at the Kennedy Center in Washington, D.C., in March 2025.

pace.oceansciences.org/wave_space_to_ocean.htm · UMD coverage of the Kennedy Center premiere

Personal Project

• •Built and shipped a mobile-first, browser-based life simulation game where players age a character year by year through careers, relationships, finances, and procedurally generated life events.
• •Separated deterministic game systems from authenticated OpenAI narrative generation behind a Supabase Edge Function.
• •Validated bounded requests and model output at the server boundary while keeping provider credentials out of the browser.
• •Wrote 350+ automated test assertions across the game engine, LLM integration, and market modules using Vitest.
• •Live at simlyfe.vercel.app — React 19, Vite, Firebase cloud saves, Supabase Edge Functions.

simlyfe.vercel.app · github.com/xmike04/SIMLYFE

M.S., Artificial Intelligence (Machine Learning concentration)

• Applied Artificial Intelligence — search, heuristics, problem solving
• Advanced Machine Learning — supervised/unsupervised learning, deep learning fundamentals

B.S., Computer Science — GPA: 3.25 (4.0 Scale)