Aug 2023 – Jun 2024 · 10 mos · Bengaluru, Karnataka, India · On-site

• Medical Document Summarization and Information Extraction
• · Developed a Generative AI pipeline to automate the manual processing of scanned medical
• documents utilizing LLM models like Llama and Claude, producing medical chronologies and
• narrative summaries. This AI pipeline, incorporating human-in-the-loop verification, achieved an
• 80% reduction in processing time and a 60% decrease in operational costs.
• · Deployed open-source LLMs, such as Llama 3, in an on-premises GPU environment utilizing
• Ollama and Docker. Conducted iterative Prompt Engineering to fine-tune the LLM’s responses
• based on feedback and specific use cases, achieving an impressive accuracy rate of 88%.
• · Designed and developed a scalable RAG pipeline using the LangChain framework and Milvus
• vector database to efficiently extract targeted information, resulting in a remarkable 90%
• reduction in processing time.
• · Experimented with closed-source models like Claude 3 on AWS Bedrock and integrated them
• into the Gen AI pipeline using the AWS SDK Boto3.
• Standard Attribute Extraction from E-commerce Product Descriptions
• · Automated extraction of standardized information from unstructured text data scraped from
• product descriptions on various e-commerce platforms using the GPT-3.5 Turbo LLM model from
• Azure OpenAI, resulting in a 12x reduction in processing time.
• · Applied advanced Prompt Engineering techniques like Few-Shot and Chain-of-Thought (CoT) to
• fine-tune LLM responses, achieving an accuracy of 93% across 20 product verticals.
• · Developed scalable APIs using FastAPI for model inferencing and CRUD operations, deployed
• using Gunicorn with MongoDB as the storage layer. Created Streamlit interfaces for labelling and
• manual verification tasks.

Mar 2022 – Oct 2022 · 7 mos · Bengaluru, Karnataka, India

• Network Management System:
• · Designed and developed a scalable and resilient data collection system adhering to design
• principles and business processes.
• · Automated the process of configuring the Telegraf agent by asynchronously connecting to a
• device inventory database in PostgreSQL using Python for reliable data collection.
• · Developed a vulnerability database by automating the collection of CVE details of
• network assets from multiple data sources through web scraping using Selenium and utilized MySQL
• database for storage.
• · Developed a frontend user interface for an interactive and self-explanatory Network Map for
• devices of the onsite infrastructure using HTML5, CSS3, and JAVASCRIPT(REACT).
• . Collaborated with cross-functional team members and worked on integrating different services into
• Django application and defining the API endpoints.

Apr 2021 – Aug 2021 · 4 mos · Bengaluru, Karnataka, India · Remote

• Taught algorithmic thinking and programming in python to students from various countries. Worked as a team member in assisting the enrollments of students to their courses with live demo session for conveying the trust of excellence with respect to curriculum.
• Initially with 1 or 2 sessions(an hour) per day ,went on teaching students with personal assistance to their clarifications and reached the count of 8 to 9 sessions per day,160 to 170 sessions per month,mentoring them on their academics on a stretch for 5 months.