AI Engineer with less than a year in Machine Learning, NLP, and Computer Vision.
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Kavya Dari is an aspiring AI Engineer with a strong academic record and practical experience in developing AI-powered systems. Currently pursuing a Bachelor of Technology in Computer Science and Engineering, she possesses expertise in Machine Learning, Deep Learning, NLP, and Computer Vision using Python and PyTorch. Her project work demonstrates proficiency in RAG systems, sign language recognition, and agentic conversational AI, showcasing her ability to build intelligent solutions and optimize performance.
Bennett University
Bachelor of Technology · Computer Science and Engineering
August 1, 2023 – June 30, 2027
Aditya Birla Public School
Class XII
June 1, 2022 – May 31, 2023
Aditya Birla Public School
Class X
June 1, 2020 – May 31, 2021
Gita Margdarshi – AI-Powered Spiritual Guidance System
September 1, 2025 – June 1, 2026
Built a RAG-based system to retrieve relevant Bhagavad Gita verses using semantic search and generate grounded responses using LLMs. Designed a data pipeline converting raw JSON into structured JSONL for efficient embedding and retrieval. Implemented vector search with ChromaDB and optimized retrieval using text chunking (400 size, 50 overlap). Developed a LangGraph workflow + FastAPI backend to enable multi-step reasoning and low-latency conversational responses.
View ProjectSanketNet – Sign Language Recognition System (Research Implementation)
June 1, 2025 – June 1, 2026
Implemented a research-based sign language recognition system using pretrained deep learning models beyond baseline CNN. Trained models on 71,000+ labeled images across 34 gesture classes, achieving up to 99.2% accuracy. Designed a hybrid fusion architecture (ResNet + ViT), improving performance to 99.31% accuracy. Enhanced model generalization using data augmentation, regularization, and evaluation metrics (precision, recall, F1-score).
View ProjectGoodFoods – AI Reservation Agent
March 1, 2025 – June 1, 2026
Built an agentic conversational system using OpenAI function-calling for restaurant search and reservation. Designed a two-stage LLM pipeline enabling tool selection, API execution, and response synthesis. Applied prompt engineering and few-shot learning to improve tool reliability and reduce incorrect calls. Developed FastAPI endpoints and a Streamlit UI to visualize tool traces and reasoning steps.
View ProjectLeetCode Rating: 1548 with 300+ problems solved
LeetCode
June 1, 2026 – Present
Dean's Award for Academic Excellence
Bennett University
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's projects demonstrate a strong interest and initiative in cutting-edge AI technologies, aligning well with an innovative and research-driven culture. The diversity of projects (RAG, Sign Language Recognition, Conversational Agents) shows a broad technical curiosity. However, without information on collaborative projects or extracurricular activities, assessing team collaboration and broader cultural fit is limited.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on complex technical challenges independently. The academic nature of projects suggests a strong learning aptitude and research-oriented mindset. However, without professional experience or psychometric test results, it's difficult to assess operational fit, teamwork, or stress handling capabilities.