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anjum_zahid

Anjum Zahid

@anjum_zahid

AI and ML Engineer

Pakistan
Anglais, Ourdou
Certaines informations sont présentées en anglais.
À propos de moi
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.... Plus d’infos

Compétences

a
anjum_zahid
Anjum Zahid
hors ligne • 
Temps de réponse moyen de 5 heures

Voir mes services

Deep learning
I will custom ai, machine learning and deep learning solutions
De100 $US / projetPlus de détails
Développement de chatbots d'IA
I will build ai whatsapp and multi platform chatbots
De30 $US / projetPlus de détails

Portfolio

Expérience professionnelle

Self-Employed

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

Self-Employed • Temps plein

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 • Temps partiel

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.