Sujanya S

AI Engineer with four live-deployed production applications spanning CNN-based computer vision, RAG pipelines, and LLM-integrated tools. Experienced across the full AI engineering stack from model architecture design, transfer learning, and hyperparameter tuning to FastAPI REST APIs, vector database integration (FAISS, ChromaDB), and cloud deployment on AWS and Render. Proficient in Python, TensorFlow, PyTorch, and SQL, with strong skills in debugging, structured output validation, context window management, and CI/CD-aware modular system design.

Data Scientist Intern at Dr. Agarwal's Eye Hospital, Clinical Research (2024-05 – 2024-06)

Structured Research Internship

• Built deep learning workflows for medical image classification using TensorFlow and Keras in a clinical research environment, improving model accuracy from a 60 to 67 percent baseline on 1,000 plus medical images through iterative preprocessing, augmentation, and CNN architecture optimization.
• Applied hyperparameter tuning and data augmentation strategies to improve model generalization across diverse medical imaging conditions.
• Collaborated directly with the clinical research team at Dr. Agarwal's Eye Hospital to translate model outputs into actionable insights; developed Python-based reporting and visualization workflows to communicate performance metrics and KPIs to medical stakeholders.

B.Sc. in Data Science and Analytics – Jain (Deemed-to-be) University, Bengaluru (2022 – 2025)