NVK

NVS VIJAY KALYAN

AI Engineer

https://www.opentalent.in/nvs-vijay-kalyan

AI Engineer with less than a year in Machine Learning, Deep Learning, and Full-Stack Development.

Key Strengths

Strong foundational knowledge in AI/ML concepts, including CNNs, Transformers, and RAG architectures.
Practical experience in developing full-stack AI applications, demonstrated by projects like the Disease Prediction System and Image Classification System.
Proficiency in key AI/ML frameworks and libraries such as TensorFlow/Keras, Scikit-learn, LangChain, and Ollama.
Experience with MLOps concepts, as indicated by certifications and project deployments using Docker.
Exposure to various deployment tools and cloud platforms (Docker, Vercel, Render) for AI applications.

Cultural & Operational Fit

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.

AI is analyzing your overall score…

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

About

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.

Top Skills

PythonSVMDockerchromadb

Education

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

Projects

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

Certifications

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

Key Strengths

Strong foundational knowledge in AI/ML concepts, including CNNs, Transformers, and RAG architectures.
Practical experience in developing full-stack AI applications, demonstrated by projects like the Disease Prediction System and Image Classification System.
Proficiency in key AI/ML frameworks and libraries such as TensorFlow/Keras, Scikit-learn, LangChain, and Ollama.
Experience with MLOps concepts, as indicated by certifications and project deployments using Docker.
Exposure to various deployment tools and cloud platforms (Docker, Vercel, Render) for AI applications.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit