Hey 👋 I’m Sena Oz.

Software Engineer

I am a Software Engineer passionate about creating impactful products. Always eager to learn and grow, I earned a Bachelor's degree in MIS from Bogazici University and pursued a Master's in Software Engineering. Currently, I work at Maestra.ai, contributing to innovative solutions.

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Experience

  1. Jul 2024 – Present

    Maestra.ai

    Software Engineer

    • Engineer scalable integrations with third-party APIs (ElevenLabs, Firebase) and distributed systems, optimizing data processing workflows and improving system reliability.
    • Design and implement modern UI components and backend services, applying algorithmic problem-solving to reduce task completion time by refactoring legacy code and decreasing technical debt.
  2. Aug – Oct 2023

    California State Uni., Silicon Valley Campus

    Software Engineer

    • Built an interactive code feedback platform using React, TypeScript, and Tailwind CSS, leveraging data structures and algorithm optimization to improve student learning outcomes by 35%.
    • Designed and implemented a RESTful API with Node.js to process real-time code submissions, applying software engineering best practices for scalable web application development.
    • Integrated machine learning capabilities via OpenAI API to generate intelligent, context-aware code feedback, demonstrating adaptability in learning and implementing AI technologies.
    • Led complete project lifecycle from design to deployment, collaborating with faculty and students to deliver a production-ready educational tool.
  3. Nov 2022 – Nov 2023

    Orion Innovation

    Junior Software Engineer

    • Built reusable components in React with TypeScript and SCSS for enterprise portals, ensuring consistency across web and mobile platforms.
    • Implemented comprehensive test coverage, including screenshot tests for visual regression and unit tests for functionality validation, ensuring stability and reliability of UI libraries.
    • Enhanced company-specific user interface libraries by resolving critical issues and developing new features based on stakeholder requirements.
  4. Mar 2021 – Jan 2023

    YetGen

    Web Application Dev., Team Lead

    • Led the development of a custom LMS that replaced a $2K/month solution and boosted course completion rates by 50%+.
    • Designed and implemented an authentication module using JavaScript and Next.js, supporting secure access for 3,500+ active users.
    • Reduced Azure and AWS deployment costs by 35% through optimized resource utilization and efficient infrastructure management.
  5. Jul – Aug 2022

    Univerlist

    Front-end Engineer Intern

Projects

  1. The Hive — Community Time-Bank Platform

    • Full-stack web platform enabling users to exchange services using time credits.
    • Built with React (TypeScript), FastAPI, and MongoDB.
    • Features include service listings with geospatial search, a community forum with WikiData-powered semantic tagging, real-time chat, 'time-credit transactions', and an admin moderation panel.
    • Deployed via Docker and GitHub Actions CI/CD to a cloud host.
    • Companion Android app built with Kotlin and Jetpack Compose.
    GitHub ↗

  2. Scholar Radar: Academic Paper Recommendation and an LLM Reranking Audit

    • Built Scholar Radar as a Graduate Research Project at Boğaziçi University: a recommender that monitors followed institutions on OpenAlex for new papers and lists the Boğaziçi researchers who work on each paper's topic (7,822 cleaned works, 3,648 researchers).
    • The research question was whether reranking embedding-retrieved candidates with a small local LLM improves recommendation.
    • A first benchmark suggested it did (MRR 0.84 vs. 0.51); an audit of that evaluation found nine problems, chief among them that cited papers were always shown to the LLM first.
    • On a rebuilt, leak-free benchmark (118 test queries, 13 methods, five shuffle seeds, Holm-corrected tests), Qwen3-Embedding-8B reached 87.0% R-precision against 43.9% for listwise Llama 3.2 3B, which largely copied its input order: the same model scores MRR 0.95 with cited papers first and 0.33 with them last.
    • The conclusions held on an 11,967-paper corpus with unit-tested leakage rules and on expertise ratings from 58 researchers, so the LLM stage was removed and the system now uses a single embedding stage.
    • Paper draft: "Do Small Local LLM Rerankers Help Scientific Paper Recommendation? An Audit and Re-evaluation with Citation and Human Expertise Labels."
    • Stack: OpenAlex, FastAPI, PostgreSQL/pgvector, llama.cpp, React, TypeScript, Docker.
    GitHub ↗

  3. Forecasting Model in Pharma Product Sales

    • Developed a forecasting model for pharmaceutical product sales using Python.
    • The model will be instrumental in predicting future sales, enabling the company to optimize inventory management and production planning.
    • The project aims to enhance the company's decision-making process, ensuring a more efficient and cost-effective supply chain.

  4. House Price Prediction Platform (Model&Frontend)

    • Created as part of the Decision Support Systems course, the King County house price prediction model addresses distrust in traditional real estate methods prevalent among Americans.
    • The project utilizes real estate market data for King County, employing regression analysis to reveal insights into the factors influencing home prices.
    • By providing data-driven decision support, the model aims to empower homebuyers and bridge the information gap in the King County housing market, fostering a more informed community.
    GitHub ↗

  5. Code Feedback and ML Model Training Platform

    • In the pipeline, I worked on the development of a cutting-edge online code-running platform using a tech stack that includes ReactJS, Tailwind, and Typescript, seamlessly integrated with the ChatGPT API.
    • What sets this project apart is its innovative approach to gathering invaluable feedback on user-written code, which will be instrumental in refining machine learning models.
    • I designed and implemented a RESTful API using Strapi, ensuring a seamless user experience and robust backend functionality.
    • The project is set to revolutionize the way developers receive feedback on their code, offering real-time insights and enhancing the learning experience.

  6. Covid-19 Tracker Application

    • Created a user-friendly Covid-19 tracker using React, Redux, Tailwind CSS, and TypeScript.
    • The app provides global and country-specific case data, features an interactive world map, and ensures smooth performance through efficient state management and Docker deployment.
    GitHub ↗

  7. Real Estate Scraper

    • Developed a web scraper that extracts information from a real estate listing website using BeautifulSoup, Pandas, Requests, and Numpy, and saves the extracted data in an excel file.
    GitHub ↗

  8. Course Registration System

    • Developed a web-based course registration system using vanilla JavaScript, PHP, and MySQL.
    GitHub ↗

  9. Find My ID

    • Built the authentication module (username & password reset tool) for a web system using JavaScript, Tailwind CSS, and Next.js.

  10. Coursera-like System

    • Built a system (WordPress, Airtable, and Moodle) that replaced a solution costing $2K/month, and increased course completion rate by 50%+.

Skills

Languages
JavaScriptTypeScriptPythonJavaSwiftUISQLNodeJSHTMLCSS
Frameworks/Libraries
ReactNext.jsReduxFastAPIStoryBookStrapiCypress
Tools
GitGitHubDockerSentryDatadogCloudflareJiraConfluence
Others
RESTful APIAgileScrumAWSGoogle CloudAzureMySQLPostgreSQL