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anjum_zahid

Anjum Zahid

@anjum_zahid

AI and ML Engineer

Paquistão
Inglês, Urdu
Algumas informações são exibidas no idioma inglês.
Sobre mim
AI & Machine Learning Engineer | AI Chatbots | Generative AI | Agentic AI | RAG AI Engineer with 7+ years experience, specializing in AI Chatbots, Generative AI, Agentic AI, and RAG pipelines. I build scalable LLM-powered applications using Python, FastAPI, LangChain, LangGraph, FAISS, and OpenAI. Expertise in vector databases, semantic search, automation, and production deployment with Docker and AWS. Let’s build intelligent AI systems that scale.... Saiba mais

Habilidades

a
anjum_zahid
Anjum Zahid
offline • 
Tempo médio de resposta: 9 horas

Conheça meus serviços

Deep learning
I will custom ai, machine learning and deep learning solutions
A partir deUS$ 100 /projetoMais detalhes
Desenvolvimento de chatbots de IA
I will build ai whatsapp and multi platform chatbots
A partir deUS$ 30 /projetoMais detalhes

Portfólio

Experiência profissional

Self-Employed

AI & Machine Learning Engineer | Generative & Agentic AI | NLP

Self-Employed • Período integral

Sep 2023 - Present • 2 yrs 8 mos

-Built Agentic AI systems using LangGraph, MCP tool calling, and RAG, including healthcare compliance analysis (FDA/WHO, medical documents, imaging) and a conversational medical lab booking platform with FastAPI and Streamlit. -Developed LLM-powered applications with LangChain, LangGraph, FastAPI, and vector databases for automation, chatbots, and PDF QA systems. -Implemented RAG pipelines using Google Gemini, Qdrant, and document processing workflows. -Created AI automation workflows with LangGraph and MCP, integrating external APIs and LLMs (OpenAI, Groq). -Built AI chatbots, deployed FastAPI apps with Docker and CI/CD, and trained deep learning models (U-Net, ResNet50) for vision tasks.

Automation Engineer

Public Sector Utility Company • Meio período

Jan 2019 - Present • 7 yrs 4 mos

Automated critical processes BOQ, billing and cost estimation using Python, significantly reducing manual effort and improving accuracy. Developed ML models and analytical dashboards for energy usage prediction, performance analysis, reporting, and forecasting, driving data-driven decisions. Streamlined cross-departmental data workflows, leading to reduced inefficiencies and improved data integrity.