Step 1: Prompt Engineering & Data Generation
Designed high-quality prompt templates targeting vehicle tuning and modification domains. Leveraged Together.AI's inference API to auto-generate thousands of diverse technical questions.
Ahmet Can ÇAKIR
I'm Backend Engineer
About
Passionate about building high-performance systems, I specialize in backend engineering, AI development, automation solutions, and intelligent scraping technologies. Focused on delivering scalable, optimized and innovative solutions that blend creativity with technical excellence.
Backend Engineer | AI Developer | Automation Expert
I design and build systems that are efficient, scalable, and intelligent. From backend architectures to AI-driven applications, I transform complex ideas into robust solutions.
- Birthday: 1999
- Website: www.ahmetlab.tech
- Phone: +90 542 567 5487
- City: Ankara, Türkiye
- Age: 26
- Degree: Bachelor of Computer Programming
- Email: [email protected]
- Freelance: Available
With hands-on experience in building backend APIs, AI model integration, real-time scraping bots, and automation pipelines, I deliver projects that push boundaries. I combine creativity and technical rigor to craft smart solutions for evolving challenges. Always learning, always building, always pushing limits.
Skills
A comprehensive skill set combining backend expertise, AI engineering, and full-stack automation.
PHP 100%
Python 75%
JavaScript 75%
Node Js 80%
Machine Learning 75%
Web Scraping 100%
Resume
Sumary
Ahmet Can ÇAKIR
Experienced Backend Developer with a strong background in developing real-time applications, web scraping, and machine learning models. Proficient in various programming languages and frameworks with a solid understanding of database management. Seeking a remote backend developer position to leverage my expertise in Python, Node.js, PHP, and other technologies to deliver high-quality software solutions.
- Ankara, Turkey
- +90 (542) 567-5487
- [email protected]
Technologies Used
Programming Languages
Python, PHP, JavaScript, C#, Java
Frameworks & Libraries
Node.js, Express.js, Flask, FastApi, Spring Boot, .NET Core, CodeIgniter, Bootstrap, jQuery
AI & Machine Learning
Hugging Face Transformers, TensorFlow, PyTorch, Keras, Tesseract OCR, OpenCV, Scikit-learn
Web & API
RESTful APIs, WebSockets, WebRTC, FastAPI, JWT, OAuth2, SOAP
Tools & Automation
Selenium, BeautifulSoup, GitHub Actions, PM2, FFmpeg
Testing & Monitoring
Postman, Swagger (OpenAPI)
Databases
MySQL, MongoDB, PostgreSQL, SQLite, Redis
Cloud & DevOps
Vercel, Cloudflare Workers, Hugging Face Spaces, Docker, Nginx, Apache, Firebase, GitHub Actions, Netlify, AWS
Other Tools
3CX IP PBX, Google Cloud APIs, OpenAI API, Arduino, Linux CLI
Professional Experience
Backend Developer
2024 - 2025
Scholege | Online Education
Developed an online lesson platform using WebRTC with functionalities like screen sharing, recording, and encrypted rooms for secure multiple participant sessions. Developing APIs with microsevices architecture for a student- teacher-university system.
Full Stack Developer
2023 - 2024
Başkent University Hospital | Healthcare Sector
Developed a real-time video consultation system between patients and doctors using WebRTC. Implemented a notification system using PHP and developed an NLP API in Python for automatic responses and AI model training.
Software Developer
2017 - 2022
INC Software Innovations | Software Consultancy
Developed AI bots using Python (Selenium, BeautifulSoup, OpenCV). Worked as a FullStack Developer using PHP (OOP), Codeigniter, jQuery, MySQL (PDO), Bootstrap, ChartJS, REST API, SOAP, Google Cloud API, and 3CX IP PBX. Worked on a real-time object recognition project using Python (Tensorflow, Pytorch, Theano, Caffe, Cntk, OpenCV) and later transitioned to C++ for better performance.
Education
Management Information Systems (MIS)
2023 - Present
Anadolu University
Computer Programming
2018 - 2020
Baskent University
LLM Project Pipeline
Step 2: Dataset Expansion via Automated Answering
Developed a Python-based pipeline that systematically queried and collected AI-generated answers, resulting in a multilingual, domain-specific dataset exceeding 5,000 Q&A pairs.
Step 3: Fine-Tuning the LLM (Phi-4)
Executed model fine-tuning using Hugging Face's transformers and datasets libraries on Google Colab. Applied LoRA-based optimization for training efficiency on limited GPU resources.
Step 4: Deploying to Hugging Face Spaces
Packaged the fine-tuned model into an interactive inference app using Gradio, and deployed it seamlessly to Hugging Face Spaces for public demo access.
Step 5: Backend API with FastAPI + FAISS
Built a production-ready RAG system powered by FastAPI. Integrated FAISS vector search with dynamic content retrieval, enabling domain-aware query responses from the dataset.
Step 6: Frontend + Hosting
Designed a clean Bootstrap-based UI. Deployed the frontend to Vercel and backend to Railway, ensuring a scalable, full-stack LLM delivery pipeline.
Projects
Can you see all my public projects open sources with by links
E-commerce API
This is a RESTful API for an e-commerce platform built with Node.js, Express, and MongoDB.
Contact
Can you contact with me. Please take the message