AI Engineer with less than a year in Machine Learning & Generative AI
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AI/ML Engineer with experience developing and deploying machine learning, NLP, computer vision, and Generative AI applications using Python, TensorFlow, Scikit-learn, and LLMs. Developed and deployed end-to-end solutions with Streamlit, OCR, RAG, and YOLO-based computer vision systems. Seeking opportunities in AI/ML Engineering, Data Science, and Generative AI.
Nilgiri College of Arts and Science
Bachelor of Computer Applications
August 1, 2021 – June 30, 2024
Quadtri Technologies Pvt. Ltd.
AI/ML Data Engineer Intern
July 1, 2025 – May 1, 2026
Cochin, Kerala, India
AI Resume Analyzer
January 1, 2024 – June 1, 2026
Developed an AI-powered resume analysis application using Gemini 3 Flash Preview API for profile evaluation and personalized recommendations. Built an end-to-end pipeline to extract text from scanned and text-based resumes using OCR and PDF parsing techniques. Engineered an AI-driven recommendation engine that identifies skill gaps, evaluates job fit, and generates personalized improvement suggestions from uploaded resumes. Designed and deployed an interactive Streamlit application integrated with GitHub, demonstrating end-to-end model deployment and API integration.
View ProjectRAG PDF Assistant
January 1, 2024 – June 1, 2026
Developed a Retrieval-Augmented Generation (RAG) application that enables users to ask natural language questions from PDF documents through an interactive Flask-based web interface. Implemented semantic search using FAISS vector database and Sentence Transformers to retrieve contextually relevant document chunks. Integrated LangChain to orchestrate the retrieval and response generation pipeline for accurate PDF question answering. Built a user-friendly chat interface to display conversation history and real-time responses Using HTML, JavaScript and CSS.
View ProjectAI Chatbot Web Application
January 1, 2024 – June 1, 2026
Developed a real-time AI chatbot application using TinyLlama via Ollama for low-latency local LLM inference. Implemented prompt engineering techniques and optimized response workflows to improve LLM output quality and reduce latency to under 5 seconds. Designed a fully local LLM architecture using Ollama and TinyLlama, enabling offline inference and eliminating third-party API costs.
View ProjectAI Fluency: Framework Foundations
Anthropic
April 1, 2026 – Present
Python Data Science
Luminar Techno lab, Kochi
June 1, 2024 – Present
AI and Robotics
ICT Academy of Kerala
August 1, 2021 – Present
Cultural Fit Analysis
The candidate's project diversity, particularly in AI/ML, NLP, and computer vision, aligns well with an AI Engineer role. The personal projects demonstrate initiative and a passion for the field. The internship experience in data engineering also shows a foundational understanding of data pipelines crucial for AI. The breadth of skills listed (ML, DL, Generative AI, Visualization, Tools) suggests a versatile individual. However, the experience level is entry-level, which might require mentorship within a senior team.
Soft Skills & Operational Fit
The candidate's project descriptions indicate an ability to work on end-to-end solutions and integrate various technologies, suggesting good problem-solving and execution skills. The focus on local LLM deployment also hints at an understanding of cost-efficiency and operational constraints. However, without direct assessment data, specific soft skills like teamwork or communication cannot be definitively evaluated.