Prathamesh Kulkarni

Engineered a high-availability backend service, sustaining 99.9% uptime for over 10 million weekly events. Automated the CI/CD pipeline, cutting deployment time by 60%. Optimized PostgreSQL queries, reducing application response times by 35%. Enhanced system scalability and resilience by containerizing the application stack with Docker and orchestrating deployments with Kubernetes. Technologies used include Python, Docker, Kubernetes, CI/CD, and PostgreSQL.

Improved system performance by 15% with targeted enhancements using TypeScript and Node.js. Reduced regression bugs by 23% by developing automated testing suites for CI pipelines. Maintained a 95% issue resolution rate for production incidents within 24 hours through rigorous incident response and root cause analysis. Utilized TypeScript, Node.js, and CI/CD methodologies.

Coursework: Introduction to Deep Learning; Advanced Topics in Data Science; Advanced Data Science Seminar; Semantic Data Integration

Coursework: Introduction to Machine Learning; Data Mining & Analytics; Data Structures & Algorithms; Operating Systems; Database Management Systems; Web Technologies & Development