Muralidhar Reddy Email & Phone Number

United States

• Fine-tuned language models such as BERT, GPT-3,Hugging face modles, claude 3 using EHR datasets to better understand and handle medical data.• Developed RAG models using LangChain and integrated them with multiple LLMs like GPT-4, LLaMA, Bloom, and BioBERT.• Combined multiple LLMs to enhance information retrieval and generation, providing comprehensive responses in healthcare applications.• Evaluated and optimized models like T5 and BioBERT with healthcare-specific metrics to ensure high accuracy in EHR data processing.• Deployed AI models using Flask to integrate them seamlessly with healthcare systems and applications.• Created APIs and managed server-side functionalities to maintain robust model performance in production.• Managed vector databases like Pinecone and SQL databases for efficient EHR data storage and retrieval.• Designed database schemas, optimized query performance, and ensured data integrity and security.• Continuously improved by staying updated with advancements in AI for healthcare and integrating new models like MedPaLM.• Explored and implemented cutting-edge tools and frameworks to enhance data processing and analysis in medical contexts.

• Performed data cleaning, preprocessing, and transformation using Python libraries and langchain.• Ensured efficient data retrieval and integration related to health care data with RAG models using graph databases.• Developed Python scripts and applications for automating administrative (health care appointment) tasks for LLM bots.• Utilized AWS bedrock and service of AWS for LLM model and data handle. Text to speech model for voice recognizing in chat bot using Hugging face model. • Developed training programs and created user manuals for staff on using RAG tools and Promote engineering. • Performed data cleaning, preprocessing, and transformation using Python libraries and LangChain to ensure high-quality input for AI models.• Ensured efficient data retrieval and integration related to healthcare data by implementing RAG models with graph databases, enhancing the accuracy and relevance of information.

Tampa, Florida, United States

• Extracted different types of data using Langchain, python, beautiful soup from different resources like websites [selenium python], pdf [1000], excel, Json, SQL, datasets and so on.• Consolidated all data into Singled document and stored in local file. Text cleaning & filter the document text content to create a corpus, suitable for analysis.• Segmented the corpus into 512 chunks and converted the text into numerical representations (embeddings) using text-embedding-3-large from OpenAI for efficient retrieval.• Stored each chunk into Pinecone vector database using Cosine similarity format. Retrieve relevant document using pinecone API based on user query.• Implemented Retrieval-Augmented Generation RAG model using GPT-4 from OPEN AI to get appropriate solution based on user query and displayed to end user.• Fed the extracted relevant document from pinecone vector database to LLM model using Langchain, python, API. • Spearheading research at the forefront of cloud, AI, GenAI, and machine learning, implementing innovative methodologies to drive advancements.

Chennai, Tamil Nadu

• Created & developed different RPA bots with solution diagrams, explanations, and high-level visual representations, collaborating closely with team members to ensure seamless integration and functionality.• Collected & preprocessed data for ML projects, resulting in data sets with 95% improved quality & accessibility.• Designed & deployed machine learning micro-services in Python, utilizing the Flask framework for architecture and implementation. • Utilized Scikit,TensorFlow, PyTorch, or Keras frameworks to train ML, deep neural networks, contributing to the development of 5+ successful models.• Implemented learning rate scheduling and early stopping techniques in natural language processing models for sentiment analysis, reducing training time by 20%.• Designed and implementation of on-premises MLOps solutions, collaborating with data scientists and software engineers.• Designed, implemented, and managed ML pipelines within AWS Sagemaker for end-to-end automation of data processing, model training, validation, and deployment. • Designed, implemented, and maintained monitoring and management tools to ensure the reliability and performance of on-premises MLOps infrastructure.

Hyderabad, Telangana, India

• Implemented machine learning algorithms [base models], ensured data quality and accessibility.• Analyzed and understood ML code, adept at bug fixing and proficient in new program development.• Performed thorough exploratory data analysis (EDA) on large datasets, leading to the development of visually engaging Tableau dashboards that provided profound insights.• Engaged in continuous learning, participating in code reviews, and adhering to best practices for AI development.• Participated in troubleshooting and debugging of user issues, demonstrating commitment to reliability and performance of AI solutions.• Learned and applied AI frameworks such as Scikit learn, NLTK in developing and implementing machine learning models.

Business Analytics & Information Systems, 3.7/4 Cgpa

Activities and Societies: Student proctor & USF IT• Master of Science in Business analytics & information systems while working.

Bachelor Of Technology - Btech, Information Technology, 8.32/10 Cgpa