- Deep Learning Capability Enhancement on Kubernetes: Led cross-functional collaborations to operationalize deep learning features, resulting in notable model performance improvements.-Database Query Optimization: Developed and optimized queries for multiple databases (Netezza, Oracle, Hadoop), enhancing transaction routing and scoring mechanisms, significantly contributing to key project milestones.- Container Platform Technology Enhancement: Validated and implemented Kubeflow components on Kubernetes, enabling complex workflow orchestration and distributed deep learning model training, while adhering to strict security standards.- Data Integration and Platform Support: Streamlined the integration of critical data feeds into Kubernetes, facilitating the smooth onboarding of various projects and improving data accessibility and management.- Operational Solutions for Graph-Based Technology: Addressed key challenges in database management and query optimization, significantly improving processing efficiency and supporting advanced graph-based analytical techniques.- AI/ML Infrastructure Development and Team Support: Played a pivotal role in establishing robust AI/ML infrastructure, enabling efficient model training and data processing, and mentored new team members to enhance their workflow efficiency.

- Responsible for the development and deployment of ML solutions across different products. - Build scalable product recommendations system using neo4j knowledge graphs which help clientel to reach out to the right customers with the right offers.- Led multiple teams to successfully orchestrate data pipelines and generate valuable insights from different data sources. - Perform different POCs to interpret model predictions for stakeholders and resolve different design problems in each ML stage.

- Implemented and positioned the voice insights platform infrastructure via the ETL pipeline in AWS used for data collection and invoke algorithms. - Designed and developed annotation tool for human labeling for training speech to text model, sentiment/aspect-based sentiment, and different classification models.- Developed modules for post-processing, mapping unstructured and structured data for applications while supervised the team and implemented solutions to deliver insights via a web portal and smooth and secure transactions via REST API.

- Designed, developed, and implemented data science and deep learning models like ASR, speaker diarization in proofs-of-concept and prototypes.- Implemented Customer Journey Maps to discover Renewal or Escalation Propensity scores of the customer from past interactions by a set of rules besides providing assistance about the implementation and deployment of Agent Assist.- Designed, developed, and implemented POC for BFSI clients like TATA AIG, Reliance General, Berkadia, etc.

- Acquired data from primary or secondary data sources and performed data analysis by using statistical techniques and providing ongoing reports. Designed, built, and implemented relational databases.- Facilitated the monthly Opportunities for Improvement (OFI) meeting in addition to execution of software development for outlined work; supported, maintained, and documented software functionality, design, and architecture.- Delivered expertise in data storage structures, data mining, and data cleansing while translating numbers and facts to inform strategic business decisions.

- Collaborating and co-developing with Application UI/UX Designer. - Expertise in Web development using Django (or other MVC frameworks), JavaScript/jQuery, CSS, front-end JS Frameworks - ReactJs and HTML. - Participate in specification, design, implementation, evangelism, and support of the product, as well as improve existing features and product performance.