AI/ML Engineer | Full-Stack Developer | Research Enthusiast
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.
BS in Data Science and Applications from IIT Madras (2021-2025)
Python, JavaScript, SQL, PyTorch, Flask, Vue.js, AWS, GCP, Docker
Software Engineer (Founding Engineer) at KRISHAI Technologies, building evolvue.ai under Krish Naik
Deep Learning & Medical Imaging research at IIT Ropar in collaboration with PGIMER Chandigarh
Completed AI Agents Fundamentals certification from Hugging Face, gaining expertise in building intelligent AI agents.
Started as Software Engineer (Founding Engineer - evolvue.ai), developing GenAI products under Krish Naik's guidance. Working on backend development and DevOps.
Concluded 8-month research internship working on Deep Learning, CNNs for Computer Vision and Medical Imaging in collaboration with PGIMER Chandigarh. Used MONAI, nnUNet, CVAT, and 3D Slicer.
Set up CI/CD pipelines using AWS and GCP, collaborated with development team for production-ready code optimization.
Complete guide to deploying Flask applications on AWS EC2 using Gunicorn and Nginx for production-ready deployment.
Learn how to configure custom domains, set up SSL certificates with Let's Encrypt, and secure your Flask application.
Comprehensive list of international internship and scholarship opportunities for students in STEM fields across the globe.
Full-stack LMS integrating Generative AI with Llama3.1 for personalized learning. Features AI chatbot for doubt resolution and programming assistance. Built with Flask, React.js, MongoDB, and Ollama.
Full-stack web application with Flask backend and Vue.js frontend. Implemented Redis caching, Gmail SMTP, Celery for async tasks, and deployed on AWS EC2 with Nginx reverse proxy.
Applied image preprocessing techniques and trained CNN models for waste classification. Evaluated performance using accuracy, precision, and recall metrics. Built with Python, OpenCV, and PyTorch.
Preprocessed dataset with feature engineering and missing value handling. Trained and compared multiple ML models for fare prediction. Used Python, Pandas, NumPy, and Scikit-Learn.
Case study analyzing customer retention strategies. Cleaned dataset, performed statistical analysis, and created data visualizations. Tools: MS Excel, Pandas, NumPy, Matplotlib.
Research project on time management and productivity. Reviewed academic papers and business reports, interviewed professionals. Team-based project using Google Docs, GitHub Projects, and Canva.