Arjun Panday

• Contributing to real-time AI/ML and Generative AI projects, designing end-to-end system architectures including dataset curation (Kaggle, Hugging Face), preprocessing pipelines, model training, fine-tuning, and production deployment. • Engineering LLM-powered multi-agent systems and Retrieval-Augmented Generation (RAG) pipelines using LangChain and vector databases for document intelligence and enterprise-grade reasoning. • Integrating trained ML models into scalable Django REST APIs and deploying containerized AI services on AWS with performance monitoring and reliability optimization. • Delivering structured technical training and hands-on workshops to paid certification cohorts in AI/ML, covering model development, deployment strategies, and applied industry use cases. • Supporting institutional and government initiatives through examination invigilation, lab supervision, and participation in technology-driven public projects.

Developed applications using core Java and OOP principles Implemented concepts like inheritance, polymorphism, encapsulation, and abstraction Worked with exception handling, collections framework, and file handling

Completed project-based internship focused on real-world web technologies Gained practical experience in development tools and workflows Strengthened problem-solving and implementation skills