Tugrul Guner
About Tugrul Guner
Tugrul Guner is a Senior Machine Learning Operations Engineer with extensive expertise in MLOps, DevOps, and cloud technologies. He has held various roles in academia and industry, contributing to AI integration and automation in product development.
Work at Arteria AI
Tugrul Guner currently holds the position of Senior Machine Learning Operations Engineer at Arteria AI, where he has been employed since 2022. His role involves leveraging his expertise in MLOps and cloud technologies to enhance machine learning operations. He focuses on integrating AI-related features into products and optimizing infrastructure costs in AI model production.
Education and Expertise
Tugrul Guner has a strong academic background with degrees in Physics and Materials Science and Engineering. He earned a Bachelor of Science (BSc) in Physics from Bilkent University, followed by a Master of Science (MSc) in Physics from Izmir Institute of Technology. He completed his Doctor of Philosophy (PhD) in Materials Science and Engineering at the same institution. Additionally, he is pursuing a Master of Business Administration (MBA) at Quantic School of Business and Technology.
Background
Tugrul Guner has a diverse professional background, having worked in various roles across different organizations. He served as a Postdoctoral Fellow at the University of Ottawa and Université INRS. He also held positions as a Product Manager and Data Science Researcher at PredictNow.ai Inc, and as a Machine Learning Operations Engineer at Novisto. His entrepreneurial experience includes founding Microscobot and Quantum Future.
Achievements in Machine Learning Operations
Throughout his career, Tugrul Guner has made significant contributions to machine learning operations. He has automated CI/CD pipelines using GitHub actions and Databricks, and developed an autoscalable and load-balanced model serving API using KServe and Kubernetes. His work emphasizes the integration of AI features into products and focuses on infrastructure cost optimization in AI model production.