Summary
Natasha Sehgal is a software engineer with a decade of experience building cloud-native SaaS and ML-backed products, currently at Meta after progressive senior engineering roles at Sift. She specializes in scalable, reliable systems and has driven ML-focused initiatives such as automated rule-based labeling and synthetic labeling to improve model training pipelines. Natasha has a strong backend stack (Python, Java, Spring Boot, Django, Kafka, AWS) and practical database experience migrating ML configuration from static files to SQL to support fintech use cases. Earlier roles at Goldman Sachs and Oracle include launching a transactional banking platform and modernizing REST APIs for enterprise order management, demonstrating comfort in regulated, production-critical environments. A U.S. citizen based in Seattle, she combines product-minded engineering with hands-on implementation of data-centric features—an often underappreciated strength that helps bridge ML research and reliable production deployments.
9 years of coding experience
3 years of employment as a software developer
Bachelor of Technology Computer Software Engineering, Bachelor of Technology Computer Software Engineering at International Institute of Information Technology Hyderabad (IIITH)
Nanodegree Data Science, Nanodegree Data Science at Udacity
Oakridge International School
English, Hindi