Researcher → Machine Learning Engineer
Building production-ready ML systems for complex data challenges.
- From Research to Production: I spent years analyzing terabyte-scale data in experimental particle physics at CERN. Now, I translate that rigorous analytical mindset into scalable Machine Learning solutions.
- Current Focus: Building end-to-end ML pipelines using APIs and Docker with a focus on efficient MLOps and cloud deployment.
- Efficiency: Using modern tooling like
uvto build the fastest, most reproducible environments possible. - Learning: Advanced system architecture, Kubernetes, and Large Language Model (LLM) orchestration.
- How to reach me: [https://www.linkedin.com/in/oguz-guzel/]
- Synthific – AI Synthetic Data Generator: A zero-cost, high-speed synthetic data generation platform using Google Gemini API (
gemini-3.1-flash-lite) for converting natural language prompts into structured tabular data schemas and@faker-js/fakerfor millisecond-scale bulk row synthesis. Built with Next.js 14 (App Router), TypeScript, and Tailwind CSS, automatically deployed via Vercel CI/CD. Check out the live app https://synthific.vercel.app.