Software Engineer Ii
CurrentMLOps • Model inferencing pipeline , Model Serving and Model Training using MLFlow.• Set up the model inferencing pipeline on RTX machine using MLFlow for differenttrained / Pre-trained models for specs generation.• Worked on different models such as Dolly, FlanT5 etc.Chat on your Database• Developed a system that generates SQL queries based on user questions,executes those queries, and returns data in a tabular format.• Achieved an 80% reduction in the time developers spend creating SQL queries,significantly boosting productivity.• Implemented a feedback mechanism allowing users to dislike and correct SQLqueries they find unsatisfactory, ensuring continuous improvement and accuracy.Generative Search (RAG) • Developed a search which detects intent of user query and based on that tune theWeaviate query parameters.• Developed the indexing pipeline which fetch data from the unstructured documentssuch as word, ppt, pdfs etc.• Created a data pre-processing pipeline which cleans and create chunks for fetcheddocuments and indexed it into vector DB.• Created RESTful APIs using Django Rest Framework to facilitate seamlesscommunication for both indexing and searching processes, enhancing theaccessibility and integration of the developed functionalities. Conversational Chatbot• Utilized OpenAI to generate matrices from chat conversations, enabling seamlessintegration of conversational data into analyses.• Developed purposeful prompts in Langchain for efficient matrix construction,optimizing the process.• Leveraged conversation memory in Langchain to maintain contextual awareness,enhancing the quality and relevance of results.
