Ravi Kumawat
(He/Him)
AI/ML Professional & Full-Stack Developer
AI/ML professional with a BS in Data Science and Applications from IIT Madras. Skilled in Machine Learning, Deep Learning, LLMs, Full-Stack Development, and Medical Imaging. Experienced in Generative AI and software engineering through industry roles and research collaborations.
Adept at building production-ready applications, scalable deployments, and applying AI to solve real-world challenges. Currently contributing as a Software Engineer (Founding Engineer, evolvue.ai) at KRISHAI Technologies Pvt Ltd, Bangalore.
Work Experience
Founding Engineer
- Building EvolVue.Ai (KrishAI Labs).
- Building an AI Powered Interview Platform using LLMs, TTS, STT Models, MCP.
- Working in a team of 4 - discuss, brainstorm, design, develop, test & deploy.
Teaching Assistant
- Project Mentor & Viva Examiner for Modern Application Development I & II (CS2003P, CS2006P).
Research Intern
- Leveraged Deep Learning & CNNs for Medical Imaging (Histopathology).
- Focus on Deep Learning for Computer Vision using MONAI & PyTorch.
RLHF Freelance Specialist
- Specialized in Reinforcement Learning from Human Feedback.
DevOps Consultant
- Collaborated with Founder to make code production ready.
- Implemented CI/CD pipelines with AWS & GCP.
Head of WebOps / Full Stack Engineer
- Led WebOps team, built backend systems using Django & AWS.
- Developed REST APIs and managed team operations.
Chief Technology Officer
- Won Hackathon at BITS Pilani.
- Incubated at JECRC Incubation Center.
Event & Marketing Coordinator
- Coordinated PIWOT 2021 event.
Education
Indian Institute of Technology, Madras
Bachelor's Degree
2021 - 2025
Academic Focus Areas
Happenings
Ram Shriram Scholarship
Ram Shriram Foundation, USA
Awarded the prestigious Ram Shriram Scholarship for academic excellence.
RCAT Scholarship
Govt of Rajasthan
Awarded by Rajasthan Center for Advanced Technology, DOITC.
TATA Capital Scholarship
TATA Capital
Recipient of the prestigious TATA Capital Scholarship.
BITS Pilani Hackathon Winner
KHOJ Startup Yatra
Secured First Place at the KHOJ Startup Yatra hackathon.
Paper Presentation
Rajasthan DigiFest
Presented a research paper on Big Data Analytics.
L&T Merit Scholarship
Larsen & Toubro
Recipient of the prestigious L&T Merit Scholarship.
Head of WebOps Team
Sundarbans House, IITM
Led the technical WebOps team and served as Group Leader in the House Council.
Event Volunteer
PanIIT Alumni & Paradox
Volunteered for PIWOT (PanIIT Alumni India) and 50 Ka Funda (Paradox-IIT Madras).
Technical Writing
Deploying Flask Applications on AWS EC2
Complete guide to deploying Flask applications on AWS EC2 using Gunicorn and Nginx for production-ready deployment.
DNS Configuration, SSL, and HTTP Setup
Learn how to configure custom domains, set up SSL certificates with Let's Encrypt, and secure your Flask application.
International Internship Opportunities
Comprehensive list of international internship and scholarship opportunities for students in STEM fields across the globe.
Licenses & Certifications
45
AWS Academy Graduate - Cloud Foundations
AWS
Sep 2025
Intro to Model Context Protocol
Anthropic
Sep 2025
Deploying AWS App with Docker
Jun 2025
Getting Started with Deep Learning
NVIDIA
Jun 2025
AI Agents Fundamentals
Hugging Face
Feb 2025
ML Techniques using Numpy
IIT Madras
Jan 2025
Deep Learning with PyTorch
Coursera
Nov 2024
Google Cloud Computing Foundations
NPTEL
Nov 2024
Tech Stack
Selected Work
GenAI Powered LMS
Designed an LMS integrating Generative AI for personalized learning. Developed an AI chatbot for doubt resolution and programming assistance using Ollama and Llama3.1.
Urban Waste Management (CV)
Applied preprocessing techniques and trained CNN models for waste classification. Assessed performance using accuracy, precision, and recall metrics to optimize the model.
Show Ticket Booking Platform
Developed a full-stack web application using Flask and Vue.js. Implemented Redis caching, Gmail SMTP, and deployed on AWS EC2 with Nginx and Celery for async tasks.
Taxi Fare Prediction using ML
Preprocessed large datasets, handled missing values, and performed feature engineering. Trained multiple Scikit-Learn models and compared performance metrics for accurate fare prediction.