Naor Sabag 💾
About Naor Sabag 💾
Naor Sabag is a Machine Learning Engineer and Data Scientist currently working at Stampli in Israel. He has extensive experience in software development, particularly in integrating machine learning models into production environments and cloud infrastructure management.
Work at Stampli
Naor Sabag has been employed at Stampli since 2022, serving as a Machine Learning Engineer and Data Scientist. In this role, he focuses on integrating machine learning models into production environments. His responsibilities include developing microservices, specifically using Java Spring Boot, to facilitate model inference. This position builds upon his previous experience in full-stack development at Stampli, where he worked from 2020 to 2022, utilizing technologies such as Java, Spring, React, and DynamoDB.
Education and Expertise
Naor Sabag obtained a Bachelor's degree in Computer Science from Bar-Ilan University, where he studied from 2011 to 2014. His educational background laid the foundation for his technical skills in software development and machine learning. He has demonstrated expertise in various programming languages and frameworks, including TypeScript, C#, and Java, as well as proficiency in cloud infrastructure management using AWS services.
Background in Military Intelligence
Naor Sabag has a significant background in Israeli Military Intelligence, where he held multiple roles. He served as a Development Lead from 2018 to 2020, focusing on TypeScript development. Prior to that, he worked as a full-stack developer in various capacities from 2014 to 2018, utilizing technologies such as C#, Angular, MongoDB, and Oracle-SQL. This experience contributed to his technical skills and understanding of complex systems.
Technical Achievements
Naor Sabag has made notable contributions in the field of machine learning. He implemented a machine learning model that improved forecast accuracy by 50% by combining a Catboost classifier with neural networks. Additionally, he has engineered cloud infrastructure using AWS services like Redshift, S3, and Sagemaker, demonstrating his ability to handle large-scale data processing. His use of Terraform for constructing AWS resources showcases his proficiency in infrastructure as code practices.
Previous Roles and Experience
Before his current role at Stampli, Naor Sabag worked as a full-stack developer at Stampli from 2020 to 2022. He also held positions at Bar-Ilan University as an Assignments Grader from 2015 to 2016. His diverse experience in software development across different technologies and environments has equipped him with a comprehensive skill set applicable to his current work in machine learning and data science.