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m_danyal_

Muhammad Danyal

@m_danyal_

AI Engineer specializing in RAG, AI Agents, Voice AI and LLMs

Pakistan
Engels, Urdu
Sommige informatie wordt in het Engels weergegeven.
Over mij
I am an AI Engineer specializing in RAG systems, LangGraph AI agents, Voice AI, LLM fine-tuning, and production-ready AI backends. I build AI assistants for documents and knowledge bases, agents that use tools and APIs, voice agents for calls and booking, and custom LLM solutions using LoRA and QLoRA. My stack includes Python, FastAPI, LangGraph, LangChain, vector databases, REST APIs, and Docker. I focus on clean code, reliable integrations, testing, deployment, and clear documentation.... Lees meer

Skills

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m_danyal_
Muhammad Danyal
offline • 
Gemiddelde reactietijd: 1 uur

Bekijk mijn diensten

Verfijning van AI-modellen
I will fine tune llms with lora and qlora
VanafUS$ 35 / projectMeer informatie
AI-integraties
I will build ai voice agents and ai receptionists
VanafUS$ 90 / projectMeer informatie

Portfolio

Werkervaring

Self_Employed

AI and Generative AI Engineer

Self Employed • ZZP

Nov 2025 - Present • 11 mos

Built and maintained production-ready AI systems for real-world business use cases, including RAG chatbots, LangGraph and LangChain AI agents, voice AI assistants, LLM applications, and model fine-tuning workflows. Developed RAG systems for PDFs, documents, websites, and business knowledge bases using vector databases, embeddings, semantic search, source citations, and retrieval optimization. Built stateful and multi-step AI agents with tool calling, API integrations, memory, workflow orchestration, MCP tools, human-in-the-loop approval, and multi-agent architectures. Developed voice AI systems for inbound and outbound calls, AI receptionists, appointment booking, lead qualification, CRM and calendar integrations, call transfer, and conversation summaries. Worked on LLM fine-tuning using LoRA and QLoRA, including dataset preparation, training, evaluation, inference, and model integration. Built Python and FastAPI backends, REST APIs, database integrations, Docker-based deployments, and production AI pipelines. Focused on clean architecture, reliable integrations, testing, maintainable source code, clear documentation, and deployment-ready solutions.