Sezin Tunaboylu

Delivering strategic advisory services on advanced data science methodologies and long-term AI scaling strategies. Guiding architectural design decisions for complex, high-impact artificial intelligence solutions across multiple business domains.

Architecting and deploying scalable LLM applications and production ML models for diverse global clients. Developing robust LLM guardrails and secure AI ecosystems whilst ensuring high reliability through comprehensive performance monitoring. Providing strategic consultation on AI ethics and EU AI Act regulatory alignment.

Led MLOps and LLMOps initiatives by engineering end-to-end production pipelines using Airflow and MLFlow. Implemented automated code scoring and quality improvement workflows for ML repositories. Managed a cross-functional team of 25+ data scientists and MLOps engineers, overseeing the complete AI lifecycle from proof-of-concept through to production deployment. Spearheaded the strategic implementation of ISO/IEC 42001 standards for AI Management Systems. Successfully executed MLOps integrations for enterprise-scale banking models. Developed adaptive self-learning systems for Small Business Churn Prediction, focusing on retraining automation and

ML/AI/DL Manager 5 performance stability to ensure consistent model accuracy over time. Managed EU-funded Horizon 2020 projects focused on predictive maintenance and decision support systems. Deployed large-scale analytics and state-of-the-art models on Azure ML platforms, building and maintaining Azure ML Pipelines for anomaly detection and fraud detection applications. Led software development initiatives using Python, C#, and .NET frameworks, integrating ERP systems with production-ready web services. Managed comprehensive SQL Database implementations including Views, Procedures, and Triggers within Azure DevOps