Summary
Sainag Shetty is a Senior Machine Learning Engineer with a decade of experience building production-ready ML systems and data-driven applications, currently at Apple after progressing from Machine Learning Engineer roles. He blends deep learning research—developing autoencoders, U-Nets, and GANs for medical imaging—with practical engineering skills in Python, C++, Kubernetes, Docker, and cloud platforms to ship scalable services. His background includes research collaborations with Stanford Medicine and hands-on product work at Lucidworks where he containerized modules, exposed deep models via REST APIs, and built a Rasa-based chatbot with speech interfaces. Comfortable across the full stack, he ties model development to deployment pipelines (Kubeflow/Kubernetes) and has repeatedly reduced environment and deployment friction. Known for translating research prototypes into robust, deployable systems, he brings both academic rigor and product-focused execution to ML and data science challenges.
10 years of coding experience
3 years of employment as a software developer
Grade 1 to Grade 12, Mathematics, Physics, Chemistry and Computer Science, Grade 1 to Grade 12, Mathematics, Physics, Chemistry and Computer Science at Sri Sathya Sai Institute of Higher Learning
Master's degree, Computer Science, Master's degree, Computer Science at North Carolina State University
Bachelor’s Degree, Computer Engineering, Bachelor’s Degree, Computer Engineering at University of Mumbai
Tulu, Hindi, English