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