Making Google Search faster and more reliable !!!

1. Building sustainable and scalable software solutions that make use of Machine learning/Deep learning technologies to scale the implementation of the Defect Elimination System, which ensures that the data in Amazon's catalogue is correct, complete, and sufficiently detailed to give customers a consistent and positive shopping experience.2. Working extensively to improve the efficacy of existing software solutions, accomplished 95% automated defect corrections of all Retail Business Catalogue defects.3. Designing the Sherlock platform, which creates automated workflows to rectify or backfill erroneous catalogue attribute data at scale.4. Working closely with other technical teams on maintaining multiple products and services, creating process automation scripts, monitoring and handling ad-hoc operational asks.5. Technology Stack Using :- Java Tech Stack, Rest Web Services, Python, Kubernetes, CI/CD, AWS, JavaScript/TypeScript.

1. Designed and executed an internal custom file delivery and management tool called RTFB ( Real Time File Broadcast ) for automated processing systems amidst continuous integration and delivery.2. Integrated the RTFB tool with features like MFA (Multi-Factor Authentication) , Multi-Part Upload , Server Side Encryption and made the file broadcasting within the organisation more secure and reliable.3. Technology stack used:- Java, Spring, Hibernate.

Worked as a full stack software development engineer, my responsibilities include:1. Development of the communication between the backend (which is a Machine learning engine) and the frontend.2. Development of Frontend applications.(Designing web app pages, dashboards etc)3. Development of automation scripts for automating different processes .