Preetham V

I’m an AI & ML undergraduate (graduating Aug 2026, CGPA 8.1/10) with hands-on experience in Python, Kotlin/Android, and Generative AI development. I built a sentiment analysis model achieving 92% accuracy and a recommendation engine that drove a 15% uplift in user engagement. I’ve delivered four end-to-end projects across computer vision, NLP, LLM workflows, mobile, and full-stack development.

In my Android App Development Intern role (Feb 2026 – May 2026) at MindMatrixEd, I engineered and shipped Android app features using Kotlin, Jetpack Compose, and Firebase—contributing to 3+ UI screens from wireframe to production. I integrated Google AI Studio GenAI workflows into mobile app prototypes and designed Firebase-backed real-time data workflows following MVVM for clean, scalable, maintainable code. I also identified and resolved 10+ bugs across app modules during iterative testing cycles.

As an AI & Data Analytics Virtual Intern (Jul 2025 – Aug 2025) with AICTE – Shell Edunet (Skills4Future Program), I built and evaluated two end-to-end AI/ML data analytics pipelines in Python on real-world green-energy datasets. Using scikit-learn and Pandas, I applied regression and classification models to produce actionable sustainability insights across 3,000+ data points.

Right now, I’m building CareerCraft AI, a full-pipeline job application assistant that parses resumes and JDs, scores keyword match across 50+ job categories, detects missing skills, and generates tailored cover letters and interview prep questions using LLM workflows. I’m also developing WasteWise (on-device waste classification with TensorFlow → TensorFlow Lite for fast inference at 89%+ accuracy) and Virasat-Namma Guide (offline-first QR check-in with multilingual storytelling), and I led a Flask + NLP claim verification pipeline in RapidVerify with sub-2s API latency. I’m drawn to teams where I can ship practical AI end-to-end—mobile, cloud, and LLM workflows included.