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IremOztimur/README.md

Hi, I'm İrem Öztimur

Generative AI Solutions Architect & Engineer

Profile views Portfolio About Me

I build intelligent, end-to-end AI systems, focusing on translating complex concepts into practical, scalable products. My expertise lies in creating robust agentic systems, sophisticated RAG pipelines, and multimodal AI applications.

Recently, I architected and led the development of a multi-agent virtual assistant for a major enterprise in the healthcare sector. The system integrates intelligent chat, video consultations, and a real-time management dashboard. My contributions spanned the full project lifecycle:

My key contributions included:

  • 🧠 System Architecture: Designed a multi-agent framework using LangGraph to handle distinct tasks like triage, video calls, consultation, and information retrieval.

  • 📚 Data Intelligence: Engineered a high-performance RAG pipeline with ChromaDB to provide agents with accurate, context-aware information.

  • ⚡ Real-Time Backend: Built the WebSocket infrastructure to power the live chat and call center monitoring dashboard.

  • 🗂️ Data Modeling: Designed the database schemas for managing user sessions, appointments, and analytics.

  • 🐳 Deployment: Implemented a fully Dockerized architecture for the FastAPI backend, Ollama model serving, and Next.js frontend.

  • 🎨 Full-Stack Development: Owned the complete build, from the Python backend to the Next.js/Tailwind user interface.

🧩 Areas of Expertise

  • Agentic AI Systems: Architecting multi-agent frameworks for complex, automated workflows.

  • Retrieval-Augmented Generation (RAG): Building robust pipelines that ground LLMs in external knowledge.

  • Multimodal AI: Integrating models like PaliGemma and CLIP to process and understand both text and images.

  • End-to-End AI Products: Bridging the gap between a Python-based ML backend and a polished, scalable web application.

  • MLOps & Deployment: Containerization with Docker, CI/CD, and cloud-native deployment.

🛠 My Toolkit

LangChain LangGraph ChromaDB
FastAPI Django Next.js React
Docker DigitalOcean
Python C C++

Beyond the Code

When I'm not architecting AI systems, you can find me performing as a live-coded musician under the name Aviara. I create algorave sets by combining Strudel (for music) and Hydra (for visuals).

I'm also deeply exploring the intersection of human-computer interaction, with a keen interest in Brain-Computer Interfaces (BCI) and the future of neurotechnology.

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  1. Turkish-Sign-Language-Recognition Turkish-Sign-Language-Recognition Public

    Recognize and interpret Turkish Sign Language gestures using machine learning. Includes tools for data collection, training, and real-time gesture detection. Built with TensorFlow and Python.

    Jupyter Notebook 4

  2. Multilayer-Perceptron Multilayer-Perceptron Public

    Implementation of a Multi-Layer Perceptron (MLP) from scratch to learn the fundamentals of neural networks. Features manual forward propagation, backpropagation, and gradient descent.

    Python 1

  3. fashionistai fashionistai Public

    Generate personalized fashion designs and find similar items online with AI. Combines image generation, segmentation, and reverse image search. Built with Python and Django.

    TypeScript 1 1

  4. 42-Handbook 42-Handbook Public

    A collection of projects from the 42 curriculum, highlighting skills in algorithms, system programming, web development, and AI. Built with C, C++, Python and Docker.

    C

  5. RayTracer RayTracer Public

    Ray tracing engine for rendering 3D scenes into 2D images. Supports basic lighting, shading, and material properties.

    Python 2

  6. AI4Robotics AI4Robotics Public

    Python implementation of Kalman Filters (KF) and Extended Kalman Filters (EKF) for robotics applications, including SLAM and localization examples. Features interactive visualizations and detailed …

    Python 1 2