Deployed LLMs using Azure Databricks, optimized model performance, and addressed system-level bottlenecks.Developed Generative AI applications with Langchain, PGVector, Pinecone, and AzureML.Implemented dynamic UI components for email section identification, utilizing Node.js for backend support.Utilized PEFT and LoRA methods for NLP and computer vision, reducing computational overhead by 25%.

Experienced using AI tools, Azure OLTP systems record business interactions as they occur in the day-to-day operation of the organization, and support querying of this data to make statistical inferences.Prepared and documented standard operating procedures and protocols as well as required system documentation. Expertly developing and managing API integrations using python Fast API with external platforms, services, and data sources, ensuring secure authentication and error handling using distributed computing tools such as Hadoop environment with Pyspark.

Produced comprehensive reports and visualizations using Medallia, Qualtrics, and In Moment data, providing key stakeholders with clear, actionable information for strategic decision-making based on fraud transfer.Worked on Building the infrastructure required for optimal ETL/ELT pipelines to ingest data from a wide variety of data sources using Microsoft Azure technologies such as Azure Data Factory and Azure Databricks using pyspark, Hive and Hadoop HDFS in bigdata ecosystem.Designed solutions for predictive analytics and data science team members that assist them in building and optimizing our product into an innovative industry leader.

Created organized, customized analysis and visualized projects and dashboards to present to executive leadership. Experienced with primary NLP Libraries, NLP techniques, Tokenization , NER and Tools (NLTK, spaCy, Gensim) functions include text mining, text classification, text analysis, sentiment analysis, word sequencing, stop words interfaces to over larger data corpora and lexical resources.Analyzed customer complaints data using DASK and Spark to identify areas of improvement in product quality and customer service, resulting in improved customer retention and satisfaction.Experienced in users with automated image, text, and video moderation services and human review tools such as thumbnails, using Optical Character Recognition (OCR) reading text in images.