I joined ASX and am looking forward to connecting with people there. The post does not specify what ASX refers to.
I joined ASX on 2026-11-08.
I described ASX as “this platform.”
I wrote, “Looking forward to meeting folks on this platform to make meaningful connections.”
My experience includes AI-agent development and internships in generative AI, artificial intelligence, and machine learning.
I worked as a Trainee Software Developer | AI Agents Team at EddyTools Tech Solutions (May 2026 to Aug 2026).
I worked as a Google Cloud GenAI Intern at Google Cloud Skills Boost (Apr 2025 to Jun 2025).
I worked as an Artificial Intelligence Intern at TechShikSha (Sep 2024 to Oct 2024), Bangalore Urban.
I worked as a Google AI/ML Intern at Google for Developers (May 2024 to Jul 2024).
I describe myself as an AI/ML Engineer focused on Generative AI, LLM applications, AI agents, and intelligent automation. I enjoy turning AI capabilities into practical applications that solve real problems.
- My areas of work include Generative AI and LLM integrations, prompt engineering, and AI-powered applications; agentic AI with LangGraph, agent workflows, and workflow orchestration; machine learning and computer vision with TensorFlow, deep learning, image segmentation, and classification; cloud AI with Google Cloud, Vertex AI, Gemini, and Azure AI; and AI automation, including HubSpot email automation and AI-enabled workflows.
My present major project is WebinarFlow AI, which automates webinar content creation through LangGraph, LLM integrations, and coordinated AI workflows that transform topics into structured, presentation-ready content.
I developed NailScan AI, a biomedical image analysis system for nail abnormality detection. It combines Micro U-Net segmentation and ResNet-50 classification, with preprocessing, model evaluation, and Flask-based deployment.
I have worked with an AI Agents team on HubSpot email automation, researched Generative AI models and tools across video, audio, text, and speech, and contributed to architectural design for an AI-powered client solution. My Google Cloud GenAI, Google AI/ML, and Microsoft-aligned Azure AI internship programs gave me exposure to cloud AI services, machine learning workflows, and computer vision applications.
I am interested in opportunities as an AI Engineer, Generative AI Engineer, Agentic AI Engineer, Machine Learning Engineer, or AI Automation Engineer. I want to help build useful AI products, integrate models into applications, and develop intelligent workflows. I am especially interested in teams that move beyond experimentation to build practical AI products; I enjoy exploring new technologies, solving engineering problems, and improving my ability to develop reliable AI applications.
I am developing WebinarFlow AI — Agentic AI Platform for Automated Webinar Content Creation, Present, Jun 2026.
I am building WebinarFlow AI as a multi-step AI pipeline in which specialized agents collaborate to turn webinar topics into structured, presentation-ready content. The project explores agent orchestration, LLM-based generation, and workflow automation to make content creation more efficient.
- My WebinarFlow AI development work includes designing agent workflows for research, structuring, and presentation generation; integrating LLMs for content generation and refinement; coordinating modular workflows with LangGraph; and exploring scalable architectures for production-oriented Generative AI systems. The project is giving me hands-on experience with Agentic AI, LLM applications, workflow orchestration, and practical AI products.
I developed NailScan AI, Feb 2026, Dec 2025.
I built NailScan AI as a deep-learning biomedical image analysis system for automated nail abnormality detection. Its end-to-end computer-vision pipeline combines a lightweight Micro U-Net segmentation model, with an encoder-decoder architecture and skip connections to isolate nail regions, and a transfer-learning ResNet-50 classifier for healthy and abnormal nail conditions.
I used a workflow covering image preprocessing and augmentation, model training and validation, and evaluation with accuracy, precision, recall, F1-score, and validation performance. I integrated the trained models into a Flask application that supports image upload and prediction.
I used a combination of publicly available Kaggle datasets and additional self-collected data, comprising 3,000+ images for NailScan AI training and evaluation.
NailScan AI gave me hands-on experience in computer vision, deep learning, biomedical image analysis, and end-to-end AI applications.
I worked on Smart Notify App, Sep 2024, Aug 2024.
I collaborated in a 24-hour hackathon to develop Smart Notify, an Android productivity application for intelligent notification and reminder management.
I contributed to implementing the Room Database for efficient local data persistence and worked with the team to deliver a functional MVP within the hackathon timeline. My role was Android Developer (Team Member), and the project used Kotlin, Android Studio, and Room Database.