Generative AI Engineer with less than a year in Machine Learning & NLP
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Assessing your cultural and operational fit
AI/ML Engineer focused on LLM applications, RAG systems, and backend-driven AI products. Built document Q&A systems using LangChain, FAISS, and OpenAI APIs along with deep learning projects in healthcare. Experienced with FastAPI, Docker, AWS, and retrieval pipelines. Interested in building reliable AI systems for real-world applications and large-scale data workflows.
RNS Institute of Technology
B.E. · Artificial Intelligence and Data Science
N/A – June 30, 2026
Take It Smart Pvt. Ltd
Data Science Intern
February 1, 2026 – May 1, 2026
India
TechnoHacks Solutions Pvt. Ltd
Machine Learning Intern
July 1, 2025 – August 1, 2025
India
LuminaPath - AI Retinal Disease Detection System
June 24, 2026 – Present
• Built a CNN-based retinal disease detection system trained on 36,000+ OCT images. • Increased model accuracy from 63% to 84% through preprocessing and architecture tuning. • Created a Streamlit interface for real-time predictions. • Added automated PDF report generation for prediction summaries. • Integrated backend inference pipeline using Flask.
View ProjectCuraLink - AI Medical Research Assistant
June 24, 2026 – Present
• Built an AI medical research assistant integrating PubMed, ClinicalTrials.gov, and OpenAlex APIs. • Created search and retrieval workflows for medical papers, clinical studies, and research summaries. • Added API fallback handling to maintain stable responses during service failures. • Integrated Hugging Face models for research-focused question answering and summarization. • Built backend APIs and frontend workflows for real-time research interaction.
View ProjectBrainwave RAG Assistant
June 24, 2026 – Present
• Built a RAG-based document Q&A system using LangChain and FAISS. • Created document ingestion, chunking, embeddings, and vector search pipelines. • Integrated OpenAI API for contextual response generation. • Reduced irrelevant responses through retrieval tuning and prompt improvements. • Tested retrieval quality using different chunking and embedding strategies.
View ProjectData Visualization
Kaggle
June 1, 2026 – Present
Google Cloud AI learning programs and workshops
Google Cloud AI
June 1, 2026 – Present
Data Cleaning
Kaggle
June 1, 2026 – Present
Cultural Fit Analysis
The candidate's portfolio showcases a strong interest and hands-on experience in Generative AI and LLM applications, aligning well with the target role. The projects are diverse, ranging from medical image analysis to research assistants and RAG systems, indicating a broad curiosity and ability to apply AI in different domains. The listed certifications and self-driven projects suggest a proactive and continuous learning mindset, which is a good cultural fit for fast-evolving tech environments. However, the experience is primarily academic and internship-based, which might require mentorship in a professional setting.
Soft Skills & Operational Fit
The candidate's project descriptions highlight problem-solving (e.g., increasing model accuracy, reducing irrelevant responses), attention to detail (e.g., retrieval tuning, prompt improvements), and a structured approach to development (e.g., creating pipelines, API fallback handling). The diverse projects suggest adaptability and a proactive learning attitude. However, without direct interview data, assessing collaboration, stress handling, or communication in a team setting is not possible.