Ye Marn Aung

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Computer Science student at San Francisco State University with experience designing and delivering scalable, high-performing, and user-friendly web applications from concept to production.

Experienced in Python, Java, React, FastAPI, AWS, and AI/ML, with strong expertise in integrating ML models and AI systems into production full-stack environments.

Adept at creating responsive and accessible user interfaces, optimizing backend performance, and collaborating across teams to deliver reliable user-facing applications.

Focus

  • Engineering

    Reliable systems, APIs, and data pipelines—clarity, observability, and maintainability first.

  • Applied AI

    Production-minded ML: evaluation, iteration, and tight loops with the people who use the output.

  • Data science

    Rigorous analysis and experimentation—turning complex data into decisions teams can act on.

Education

San Francisco State University

Bachelor of Science, Computer Science (Minor in Mathematics)

San Francisco, CA · Expected December 2026

Professional Experience

AI Engineering Extern — Outamation

March 2026 – Present

  • Built an end-to-end document intelligence pipeline that classifies and extracts structured data from mortgages, invoices, and contracts using Tesseract, PaddleOCR, and EasyOCR for RAG workflows.
  • Benchmarked layout-aware parsing techniques across document formats, identifying OCR–LLM combinations that improved extraction efficiency and accuracy on multi-column and table-heavy layouts.

Project Experience

HowToKeepPlantsAlive: AI Plant Recommendation System & Care Platform

GitHub

Tech stack: LangGraph, PyTorch, Python, MongoDB, Gemini LLM, Voyage AI, Cohere Reranker, DVC, Prefect, MLFlow, Pinecone

  • Engineered a two-tower recommendation system using Feast-backed features and holdout-based offline evaluation, outperforming a cosine-similarity baseline by 6.6× on Recall@10, 3.8× on NDCG@10, and 4× on Hit@10, while reducing inference latency from 63.7ms to 2.2ms.
  • Developed a LangGraph multi-agent system for plant Q&A, side-by-side comparison, exploring recommendations, and live web search via Tavily, supported by a hybrid RAG pipeline with cosine similarity, BM25 reranking, and recursive/sliding window chunking.
  • Designed a synthetic data generation framework that simulated user–plant interactions for training and evaluation in a data-scarce domain, successfully capturing 8 out of 10 target behavioral patterns.
  • Containerized the FastAPI backend with Docker and deployed on Railway and Vercel, serving a catalogue of 1000+ plants.

GaitorGate: Full-Stack Search Engine for AI Tools

GitHub

Team Lead

Tech stack: LAMP stack, Flask, AWS EC2, Google Gemini

  • Led a team of 6 to develop a search platform for 100+ AI tools using keyword or NLP-based search, winning 1st place out of 12 teams in a software engineering competition.
  • Designed and optimized a relational database schema and search pipeline using SQL, enabling natural language queries with ~0.4s average latency.
  • Collaborated cross-functionally with designers, frontend and backend engineers, and QA in an Agile environment to improve team productivity and workflow efficiency.

Board2Board: Chess Utility Tool for Over-the-Board (OTB) Game Recognition

GitHub

Tech stack: Keras, Python, OpenCV, ResNet50, Scikit-learn, Matplotlib, SciPy, scikit-image, TensorFlow

  • Designed a computer vision pipeline with OpenCV to detect, warp, and segment real-life chessboard images into 64 cropped squares for piece classification.
  • Fine-tuned a ResNet50 model on a custom dataset of 2,000+ images, achieving 94% classification accuracy across all classes.
  • Developed an adaptive thresholding system using linear regression to handle variable lighting and image conditions, improving successful board detection rate by 4× across 150 diverse real-world unseen board images.

Skills

Programming languages: Python, Java, JavaScript, TypeScript, Rust

Databases: MySQL, MongoDB, PostgreSQL, Pinecone, Supabase

Cloud/DevOps: AWS, Azure, Docker, Railway

ML/AI: Keras, TensorFlow, PyTorch, LangGraph, LangChain, OpenCV, Hugging Face

Contact

Ye Marn Aung. Open to software, applied AI, and data science roles. For opportunities or a brief introduction, reach out by email, GitHub, or LinkedIn.

Email · GitHub · LinkedIn