m
mhr_212

Muhammad Haroon

@mhr_212

AI and ML Engineer , Deep Learning , NLP , Django

Pakistan
Anglais, Ourdou, Pachto
Certaines informations sont présentées en anglais.
À propos de moi
I’m an AI & Machine Learning Engineer with a strong CS foundation and hands-on experience building intelligent, production-ready systems. I specialize in NLP-driven applications, AI-powered automation, and scalable Django backends. Core Expertise: AI/ML: Prompt engineering, NLP chatbots, and automated hybrid decision systems. Backend: Scalable Django architecture, REST APIs, and secure, high-performance web apps. Tech: Python, PostgreSQL, Tailwind, Docker. If you need someone who can design AI logic, control model outputs, and integrate AI safely into real products, I’m ready to help.... Plus d’infos

Compétences

m
mhr_212
Muhammad Haroon
hors ligne • 
Temps de réponse moyen de 1 heure

Voir mes services

ETL de données
I will design sql healthcare data warehouse and etl solutions
De50 $US / projetPlus de détails

Portfolio

Expérience professionnelle

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Data Engineer

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Mar 2026 - Apr 2026 • 1 mo

**Achievements & Experience** Successfully completed all 5 Data Engineering tasks (200+ hours of hands-on work) within a structured internship program, delivering end-to-end solutions across diverse real-world domains: - **Real-time Streaming Analytics Platform** — Built a live data streaming pipeline using Apache Kafka and Spark, enabling real-time ingestion, processing, and analytics at scale. - **Healthcare Data Warehouse** — Designed and implemented a structured data warehouse for healthcare records using Python and SQL, ensuring data integrity, compliance-ready schema design, and efficient querying. - **E-commerce Sales Performance Data Pipeline** — Developed an automated ETL pipeline to process and analyze sales data, providing actionable performance insights across product and revenue metrics. - **IoT Sensor Data Processing System** — Engineered a high-throughput data processing system to collect, transform, and store continuous IoT sensor streams using Kafka/Spark and containerized infrastructure via Docker/Kubernetes. - **ML Model Performance Tracking** — Built a monitoring pipeline to track, log, and evaluate machine learning model metrics over time, supporting data-driven model improvement cycles. **Key Technologies Used:** Python · SQL · Apache Kafka · Apache Spark · AWS/GCP/Azure · Docker · Kubernetes