Egemen Zeytinci is an Application Architect and seasoned machine learning engineer with nine years of experience building end-to-end ML solutions across fintech, logistics, and insurance domains. He has led teams and productionized models—from warehouse workload prediction and TOPSIS-based efficiency scoring to OCR, liveness detection, and residual-value forecasting—while building data pipelines and dashboards to close the loop on model impact. Comfortable across the stack, he combines Airflow-driven ETL, vector DBs (Milvus), LLM tooling (LlamaIndex, vLLM), and React/Streamlit frontends to turn prototypes into operational products. Colleagues rely on him for clean, maintainable code and practical performance improvements such as daily-update models and outlier-stable predictions. Based in Istanbul, he brings a pragmatic blend of hands-on engineering, cross-functional collaboration, and a curiosity for applying prompt engineering and retrieval systems to real business problems.
9 years of coding experience
8 years of employment as a software developer
Bachelor's degree Computer Engineering, Bachelor's degree Computer Engineering at Sakarya University
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