Istanbul, Istanbul, Türkiye
An AI Engineer and Google Cloud GenAI Champion who bridges the gap between deep theoretical mathematics and scalable production engineering. With a strong academic background (Double Major in CS/EEE + Minor in SE from Bahçeşehir University), I specialize in the end-to-end lifecycle of AI systems—from the math behind Transformers to distributed training on Kubernetes. Core Focus Areas: Deep Tech AI: Moving beyond simple API calls to engineer autonomous AI Agents using LangChain, Google GenAI SDK, and MCP, with a deep command of LLM architecture (Attention mechanisms, tokenization). Scalable Engineering: Deploying models to production via MLOps pipelines (VertexAI, GKE) and managing large-scale Recommendation systems on Google Cloud. Community Leadership: A dedicated Open Source advocate and content creator, sharing technical expertise on global stages (Open Source Summit, South Korea) and digital platforms. Objective: To democratize access to advanced AI technologies while engineering robust, scalable, and efficient systems.
As a Google Cloud GenAI Champion working within a Premier Partner ecosystem, I architect and deploy end-to-end AI solutions that bridge theoretical research with production-grade engineering. Generative AI & Agents: Designing and developing autonomous AI agents using Google ADK. I implement advanced workflows utilizing the Model Context Protocol (MCP) for robust agentic reasoning and tool use. Distributed Computing: Orchestrating parallel LLM fine-tuning and training pipelines on Google Kubernetes Engine (GKE) using the Ray framework to optimize performance and scalability. Recommendation Systems: Engineered a full-scale recommendation engine using a Two-Tower architecture on H&M datasets. Integrated LightGBM for ranking models and deployed the serving layer on Google Cloud Run. MLOps & DevOps: Establishing robust CI/CD pipelines using VertexAI pipeline. I manage the deployment of microservices and AI models onto Kubernetes clusters, ensuring high availability and GitOps best practices.
Natural Language Processing.