I build scalable AI
& ML systems with modern web engineering
0+
Years of Experience
0K+
ML Dataset Samples
Organizations & Experience (2024–Present)
Engineering intelligent ML pipelines
and scalable web systems
with data-driven precision
AI/ML Engineer in training and Software Developer with hands-on experience building end-to-end ML pipelines
using real-world datasets (20K+ samples), model evaluation, and feature importance analysis.
Currently upskilling through a structured Data Science, Machine Learning & MLOps program at Skillianz,
with a long-term goal of contributing to scalable AI systems at top product-based companies.
Data Science, ML & MLOps Program
Skillianz • Professional Certification
2026
B.Tech in Computer Science & Engineering
UKF College of Engineering and Technology
2023
Production RAG & Vector Search System
AI Engineering Milestone • ChromaDB & Groq LLM
2026
Enterprise HRMS & Scalable REST APIs
GDMR Foundation • System Efficiency +25%
2025
CI/CD Pipeline Automation & 90% Build Reduction
DevOps & Cloud Deployment Milestone
2026
08/2026 – Present
Software Developer • GDMR Foundation (Trivandrum)
Developed high-performance web applications, improving system efficiency by 25%. Designed and deployed secure REST APIs and database models to support scalable backend services. Automated deployment pipelines using CI/CD tools, reducing weekly release times by 40%.
03/2025 – 08/2026
Junior Web Developer • GDMR Foundation (Trivandrum)
Built and maintained WordPress-based systems, including an internal HRMS using React, Python, and MongoDB. Utilized AI-assisted tools to speed up development, enhance code quality, and streamline workflows — forming a solid foundation for AI/ML engineering.
01/2024 – 03/2025
Junior Web Developer • Websorbz Pvt Ltd (Kollam, India)
Developed and maintained websites using WordPress, HTML, CSS, JavaScript. Integrated APIs, optimized performance, and improved UI/UX. Cultivated strong problem-solving and software engineering fundamentals transferable to ML systems.
Ongoing Upskilling
Data Science, Machine Learning & MLOps • Skillianz
Hands-on experience building end-to-end ML pipelines with real-world datasets (20K+ samples), model evaluation, and feature importance analysis. Goal: building scalable AI systems at top product companies.
08/2019 – 08/2023
B.Tech in Computer Science & Engineering • UKF College of Engineering and Technology
Kollam, India. Core coursework: Programming Fundamentals, Data Structures, Algorithms, Databases, Software Engineering. Strong foundation in problem-solving and computer science fundamentals supporting my transition into AI/ML Engineering.
AI Career Intelligence Platform
Full-stack web application that matches a user's resume against job postings using skill-extraction and a RAG pipeline (ChromaDB vector search + Groq LLM) with topic-scoped guardrails for AI-driven career guidance.
Year
2026 - Present
Role
Full-Stack & AI Engineer
90% Docker build time reduction • RAG pipeline • Railway & Vercel deploy
01 / 03
California Housing Price Prediction
End-to-end ML regression pipeline on the California Housing dataset (20,640 rows, 8 features). Evaluated Linear Regression baseline and Random Forest Regressor, achieving R² ≈ 0.81 and identifying Median Income as top predictor.
Year
2025 - 2026
Role
ML & Data Science Engineer
R² ≈ 0.81 • MAE ≈ 0.33 • RMSE ≈ 0.50 • 20,640 Samples
02 / 03
Enterprise HRMS & Cloud Backend Systems
High-performance internal Human Resource Management System and web platforms built with React, Python, and MongoDB. Engineered secure REST APIs and automated CI/CD deployment pipelines.
Year
2025 - 2026
Role
Software Developer • GDMR Foundation
25% System efficiency gain • 40% Weekly release time reduction
03 / 03
Machine Learning & Data Science
Design and implement end-to-end ML regression and classification pipelines. Proficient in exploratory data analysis (EDA), feature importance analysis, hyperparameter tuning, model evaluation metrics (R², RMSE, MAE), and deploying models on real-world datasets.
RAG Pipelines & GenAI Integration
Architect Retrieval-Augmented Generation (RAG) pipelines using vector databases (ChromaDB) and fast LLM inference (Groq, Gemini). Ground AI-driven advice with curated knowledge bases, structured JSON outputs, and topic-scoped guardrails.
Full-Stack Web & Scalable REST APIs
Build robust, high-performance web systems and microservices. Layered router/service/repository backends with FastAPI and Python, paired with modern responsive Next.js & React frontends, secure JWT authentication, and SQL/NoSQL databases.
Docker Containerization & CI/CD
Automate delivery workflows and containerize full-stack applications with Docker. Optimize container build times by up to 90%, configure production environment splits, and automate CI/CD pipelines to slash weekly release times by 40%.
Core technologies & frameworks
powering data pipelines & scalable systems
Python (pandas, NumPy)
Data Science, Scripting & ML Workflows
95%
Machine Learning & Scikit-Learn
Regression, Random Forest, Feature Engineering & EDA
90%
FastAPI & REST APIs
High-performance backend services & RAG pipelines
88%
React & Next.js
Full-stack frontend architecture & TypeScript interfaces
85%
SQL & Databases (PostgreSQL, MongoDB)
Relational schemas, NoSQL document stores & data modeling
85%
Docker & CI/CD Pipelines
Containerized deployments, Railway/Vercel & release automation
82%
Feedback & Recommendations
What engineering leads, mentors, and teammates say about collaborating on ML models and full-stack software.