• Contributed to the development of the new onboarding flow, increasing successful onboardings by 5%, and developed dividend processing for some Portfolios.• Optimized multiple API’s performances, reducing response times by 10-20%, and resolved various issues, enhancing the user experience

ML Platform:•Contributed in the Backend development using Python and Java, developing packages involving integration with Azure Blob Storage & Functions, SQL databases, Databricks Feature Store & MLflow, and Aerospike.Always Be Deploying - Deployment Platform:• Implemented various deployment pipeline components and compliance workflows using Python and Bash, establishing Continuous Deployment (CD), and achieving end-to-end automation for efficient, high-velocity production deployments.• Designed and implemented deployment processes for various types, including Airflow DAGs, Azure Secrets, and Flink Streaming Jobs.• Led the onboarding and management of deployment pipelines for multiple teams, ensuring seamless integration.• Responsibilities include resolving issues, debugging, conducting RCA, participating in on-call rotation, leading POC for specific components, and collaborating with teams for optimal integration and functionality.

• Developed an orientation-based detection model for ultrasound Heart view planes, implementing various orientation detection techniques using YOLOv3 model, achieving around 73% accuracy.• Analyzed the performance of the HRNet model in a classification task distinguishing between Heart and Abdomen ultrasound view planes.