Engineering Generative AI, LLM Systems & Intelligent Agents for Production 

I'm Shreyansh Jain — a Computer Science undergraduate focused on Generative AI, Large Language Models, and Agentic AI systems. I design and deploy real-world GenAI applications including RAG pipelines, autonomous agents, and fine-tuned LLMs using LoRA, QLoRA, and reinforcement-based optimization techniques. Beyond GenAI, I have hands-on experience across machine learning, computer vision, backend systems, and AI research — from building real-time vision pipelines and quantum-enhanced ML models to publishing research papers, open-source Python packages, and engineering production-scale AI projects.

My technical foundation is strengthened through MIT's OCW Algorithms and Data Structures course, Stanford's CME 295 (covering transformers, model training, fine-tuning, and agents), and certifications in Machine Learning and Deep Learning Specializations from DeepLearning.AI and Stanford. I actively explore new model architectures, training techniques, and optimization strategies, incorporating them into my work to improve performance, efficiency, and scalability. I enjoy working at the intersection of research and production, turning ideas into scalable intelligent systems.

Generative AI · LLM Systems · RAG Pipelines · AI Agents · Production ML · Research Engineering · Open-Source AI · Computer Vision · MIT OCW · Stanford's CME 295 · DeepLearning.AI