Building production AI systems, contributing to open source, and researching efficient Small Language Models.

• 🏢 AI/ML Engineer building enterprise AI systems for SAP-integrated platforms serving 10,000+ users
• 🌱 Open Source Contributor to Spring AI
• 🧠 Researching Small Language Models (SLMs) for edge devices and efficient AI
• ⚙️ Building AI Agents, MCP Servers, Enterprise RAG, Semantic Search & AI Infrastructure
• 📚 Interested in AI Systems, Retrieval, Evaluation, Distributed Agents and Efficient Training
• ✉️ yashrawal987@gmail.com

• Enterprise AI Platform Engineering
• Spring AI
• Model Context Protocol (MCP)
• Agentic AI
• Retrieval Augmented Generation (RAG)
• Small Language Models
• AI Evaluation
• AI Infrastructure

✅ Merged Contribution

• Amazon Bedrock Converse Cache TTL Support
• Spring AI 2.0.1

🚧 Active Contributions

• Reasoning Metadata Improvements
• OpenAI Integration
• Enterprise AI Features

I'm researching how capable language models can be trained with minimal compute.

The long-term goal is to make useful AI practical for:

• Raspberry Pi
• Android
• iOS
• Edge Devices
• Embedded Hardware

Current research includes

• Efficient Transformers
• Lightweight Attention
• Tokenizers
• Training from Scratch
• FragmentStream Attention
• Low-compute AI

Python • Java • Spring AI • MCP • LangChain • LangGraph • OpenAI • Claude • Gemini • Amazon Bedrock

Hybrid Search • BM25 • pgvector • FAISS • Pinecone

Spring Boot • FastAPI • Flask • PostgreSQL • SAP HANA • GraphQL

Docker • AWS • Azure • SAP BTP

🔹 Spring AI Contributions

🔹 Mini Language Model

🔹 Enterprise RAG Platform

🔹 MCP Server

🔹 AI Evaluation Framework

LinkedIn: https://linkedin.com/in/rawal-yash

Hugging Face: https://huggingface.co/Yash911

Kaggle: https://www.kaggle.com/yashrawal2001

GitHub: https://github.com/YashRL