I'm a Computer Science undergraduate at REVA University (2023–2027), based in Bengaluru, India — building at the intersection of full-stack engineering, AI/ML, and cloud-native deployment.

I specialize in designing scalable backend systems, end-to-end ML pipelines, and production-ready deployments with Docker, AWS, and CI/CD automation. I'm passionate about systems that are not just functional — but robust, efficient, and built to scale.

name        : Likhith S Gowda
location    : Bengaluru, Karnataka, India
degree      : B.Tech CSE @ REVA University (2023–2027)
focus       : Backend Engineering · AI/ML · MLOps · Cloud Deployment
available   : Internships | Full-time Roles | Open Source
contact     : likhisgowda2005@gmail.com

Language	Proficiency
Python	████████████ Advanced
JavaScript (ES6+)	████████████ Advanced
Java	█████████░░░ Intermediate
C	████████░░░░ Intermediate

  HTML5   CSS3   JavaScript (ES6+)   React.js   Tailwind CSS   Responsive Design

  Node.js   Express.js   Flask   REST APIs   JWT Auth   Microservices   Nginx   Gunicorn

  MongoDB   PostgreSQL   MySQL   Firebase   Database Optimization   Schema Design

     

  TensorFlow   Keras   scikit-learn   Deep Learning   NLP   MLflow   DVC   LLM Integration   Gemini API   Groq   Generative AI

  Docker   AWS EC2 / ECR / S3   GitHub Actions   Terraform   CI/CD Pipelines   Linux   Git   Postman

• Engineered full-stack web applications using Node.js, Express.js, and MongoDB following clean architecture principles
• Designed and built scalable REST APIs with optimized query performance and reduced response latency
• Implemented modular, maintainable codebases with Git-based collaborative workflows
• Contributed to backend infrastructure improvements that enhanced overall system performance

• Developed AI-powered applications during hands-on industrial training
• Built a Spam News Detection System using NLP and ML classification techniques
• Authored comprehensive AI project documentation; received formal appreciation for quality of work
• Gained practical exposure to AI project lifecycle — from research to deployment

AI-powered Human Capital Management platform with autonomous task orchestration

• Integrated Gemini & Groq LLMs for intelligent task assignment and workload balancing
• Built a 25+ endpoint REST API backend with RBAC, audit logging, and secure authentication
• Reduced manual task assignment overhead by ~60% through AI-driven automation
• Dockerized microservice architecture for scalable, production-ready deployment

End-to-end deep learning system with full MLOps integration

• Fine-tuned VGG16 CNN on medical imaging data using TensorFlow & Keras
• Integrated MLflow for experiment tracking and DVC for data/model versioning
• Exposed predictions via a Flask REST API with real-time inference support
• Containerized with Docker; infrastructure designed for AWS EC2/ECR deployment

Production-grade ML pipeline with full CI/CD automation

• Built complete ML pipeline with scikit-learn: feature engineering, training, evaluation
• Implemented DVC for data and model versioning across environments
• Deployed Flask app with Gunicorn on cloud with GitHub Actions CI/CD

Full-featured multi-account personal finance management system

• Multi-account expense management with secure JWT authentication
• Excel export, analytics dashboard, and advanced filtering/reporting
• Scalable MongoDB schema with optimized aggregation queries

Production-ready shopping application with full cart & order lifecycle

• Full authentication flow, cart management, and order tracking system
• Responsive React.js frontend with clean UX and smooth navigation
• REST API-driven architecture for decoupled frontend/backend scalability

 

• 🏅 Full Stack Web Development — Udemy
• 🏅 AI Applications Industrial Training — Plasmid Innovation Ltd (Letter of Appreciation)