Hi, I’m Ziraddin Gulumjanli.

I architect scalable MLOps ecosystems that bridge the gap between AI research and production-grade products. Whether it’s designing multimodal RAG pipelines or CNN-based vision systems, I build the full lifecycle—orchestrating LLM workflows with LangChain, managing experiments with MLflow, and deploying containerized FastAPI clusters on Kubernetes. My focus is shipping automated, CI/CD-driven infrastructure on AWS that doesn't just work, but stays high-performing, monitored, and cost-effective at scale.

Python Sckitlearn Matplotlib Keras PyTorch Keras Tensorflow ML Algorithms CNN LLM FastAPI Docker MLflow Airflow / Prefect Kubernetes Monitoring Prometheus / Grafana Evidently Apache Spark CI/CD (GitHub Actions) GCP/ AWS (S3)/Azure
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Latest Projects

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AutoML-Lifecycle-Monitor-for-Diabetes-dataset

AutoML-Lifecycle-Monitor-for-Diabetes-dataset

Grafana Prometheus Evidently
Practical MLOps — From Dataset to Self-Updating Model System

Practical MLOps — From Dataset to Self-Updating Model System

MLOps Monitoring
R Shiny–Based Exploration of Netflix Content Trends

R Shiny–Based Exploration of Netflix Content Trends

Rshiny R Netflix
Understanding Movie Success Through Exploratory Data Analysis

Understanding Movie Success Through Exploratory Data Analysis

EDA cinema trends
Unsupervised-learning-implementation-on-HeartAttackDataset

Unsupervised-learning-implementation-on-HeartAttackDataset

k-means tSNE PCA Hierarchical clustering
Machine Learning for Fraud Detection in E-commerce

Machine Learning for Fraud Detection in E-commerce

Random Forest Logistic Regression DBSCAN