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AI Engineer with less than a year in Machine Learning, Deep Learning, and Full-Stack Development.
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Assessing your cultural and operational fit
Highly motivated AI Engineer currently pursuing a Bachelor of Technology in Artificial Intelligence and Machine Learning. Possessing a strong foundation in Python, machine learning frameworks like TensorFlow and Keras, and full-stack development using React and FastAPI. Proven ability to build and deploy AI-powered systems through projects like a Symptom-Based Disease Prediction System and an AI-Powered Document Question Answering System, demonstrating practical application of theoretical knowledge.
Indore Institute of Science and Technology
Bachelor of Technology · Artificial Intelligence and Machine Learning
August 1, 2022 – June 30, 2026
M.G.M Senior Secondary School
Higher Secondary Education
N/A – May 31, 2022
Symptom-Based Disease Prediction System
June 24, 2026 – Present
Developed a full-stack AI-powered disease prediction system that predicts potential diseases from user-selected symptoms using a trained Random Forest model, with a FastAPI backend and a modern React-based frontend, fully deployed on cloud platforms. Frontend: Framework: React (Vite) Backend: PHP Deployment: Vercel Deployment: Dockerized & deployed on Render
AI-Based Image Classification System
June 24, 2026 – Present
Developed an end-to-end image classification system using a MobileNetV2-based CNN, FastAPI backend, Dockerized inference pipeline, and a Vite + TypeScript frontend for real-time predictions. Frontend : React, Vite, TypeScript, Tailwind CSS Backend: FastAPI, Python, TensorFlow / Keras, Docker Machine Learning : CNN, MobileNetV2, ImageDataGenerator, confidence scoring Deployment & Tools : Docker, Vercel (Frontend)
HR Automation System
June 24, 2026 – Present
An AI-powered HR automation system built with n8n that automates candidate screening, interview scheduling, resume parsing, and AI-generated email replies using OpenAI/GPT models. Framework: n8n Model: Open AI Gpt 4-0 Libraries: n8n built-in nodes (HTTP Request, Gmail, Google Calendar, Webhooks)
AI-Powered Document Question Answering System
June 24, 2026 – Present
Built an end-to-end AI-powered document chatbot using a Retrieval-Augmented Generation (RAG) pipeline with LangChain, Ollama (LLaMA 3), and ChromaDB, supporting real-time context-aware responses with semantic search over custom documents. Framework: Langchain Model: Ollama (LLaMA3) Database: ChromaDB Libraries: PyPDF, LangChain-Ollama
MLOps for Generative AI
Google Cloud
June 1, 2026 – Present
AI Agents & Automation
E Skills
June 1, 2025 – Present
AI Anomaly Detection Certificate
NVIDIA
May 1, 2025 – Present
Data Analytics
Accenture North America
January 1, 2025 – Present
Generative AI Fundamentals
DataBricks
December 1, 2024 – Present
Cultural Fit Analysis
The candidate demonstrates a strong interest in AI/ML through academic projects and certifications. The diversity of projects, ranging from disease prediction to HR automation and document Q&A, indicates a broad application interest within AI. Participation in challenges like Amazon ML and Accenture Innovation suggests a proactive and competitive spirit. However, all projects are academic, and there is no professional experience, which limits the assessment of cultural fit in a corporate environment. The candidate's focus on AI Engineer roles aligns well with their demonstrated skills and interests.
Soft Skills & Operational Fit
The candidate's resume highlights soft skills such as Communication, Critical Thinking, Problem Solving, Data Storytelling, and Collaboration. While these are crucial for operational fit, there is no direct evidence or assessment data to validate these claims. Project descriptions suggest an ability to work on end-to-end systems, which implies problem-solving and critical thinking, but the extent of collaboration or communication skills in a team setting is not demonstrated.