AI & Machine Learning
Python, PyTorch, TensorFlow, scikit-learn, Generative AI, LLM agents, RAG, Prompt Engineering, Pandas, NumPy, Power BI.
AI Engineer · Android Developer · Full-Stack Builder
Available for 2026 roles and freelance builds from Bengaluru, India. Drop your email and I'll get back with projects, case studies and a full CV.
Read the manifestoAbout Me
My Approach
Every build starts with the data and the user, not the framework. I prototype fast, measure honestly, and ship AI features that hold up in production.
How I work
From ML pipelines for churn prediction to LLM agents and Android apps, I work where applied research meets product craft — turning models and datasets into interfaces people actually use.
What drives me
Curiosity plus conviction. Every project — Sophia, J.A.R.V.I.S — NIX, LumoroX — started as a question and grew into a shipped system with real users, measurable results, and open-source code.
Projects Built
Certifications
Industry Internships
IIT Indore AI Track
AI-focused engineer turning messy data and vague product ideas into shippable, intelligent features.
Generative AI, Android UX, and edge-deployed ML — the frontier where models meet users.
Notebook prototype → deployed feature. Measure, iterate, ship without drama.
Models only count when they reach real users. Impact over accuracy metrics.
Python, PyTorch, TensorFlow, scikit-learn, Generative AI, LLM agents, RAG, Prompt Engineering, Pandas, NumPy, Power BI.
Kotlin, Java, Jetpack Compose, Android SDK, React, TypeScript, Tailwind CSS, Framer Motion, HTML5, Material Design.
Node.js, Express, REST APIs, Firebase, SQL / MS SQL, MongoDB, Supabase, Flask, FastAPI, data pipelines.
Git & GitHub, Docker, Linux, CI/CD, Vercel, Jupyter, VS Code, Android Studio, Postman.
Prompt orchestration, RAG pipelines, tool-using agents, and applied LLM workflows.
Modern Android apps with Kotlin, Jetpack Compose, and Firebase — AI features baked in.
Turning LLMs into features users love — from chat to content to autonomous flows.
React + Node + Supabase apps with clean UX and production-ready architecture.
Classification, regression, and recommender systems trained on real datasets.
ETL, feature engineering, and intelligent automation glue for internal tools.
Tool-using assistants with memory, planning, and structured outputs.
Hybrid retrieval, chunking strategies, and grounded generation.
Quantized models + edge deployment for private, low-latency ML.
A curated selection of recent work showcasing AI engineering, applied machine learning, Android and full-stack product development.
View all projectsIIT Indore · via Intellipaat
Bangalore Technological Institute · VTU · CGPA 7.5
LLM-driven flows embedded into Android & web apps with prompt orchestration.
Structured templates, evals, and guardrails for production assistants.
Classification, regression, and recommender systems on real datasets.
Currently exploring agents, retrieval-augmented generation, and on-device inference.
Have an idea? Need an AI Engineer or Android developer? Drop a message — I reply within a day.