ML monitoring platform
ModelOps Doctor
Model health, data drift, and diagnosis in one practical control room.
Machine learning engineer · Python · MLOps
Build the model. Make it usable. Keep it observable.
I work across data preparation, predictive modeling, computer vision, evaluation, API integration, and model monitoring. My focus is the path from a dataset to software people can inspect and use.
Across the model lifecycle.
Prepare and train
Python, Pandas, NumPy, feature engineering, classification and regression with scikit-learn, and deep learning with PyTorch and TensorFlow/Keras.
Evaluate and integrate
Model evaluation, hyperparameter tuning, computer vision with OpenCV, OCR and OMR processing, and FastAPI or Flask APIs for application integration.
Monitor and reproduce
Model health and drift detection, MLflow experiment tracking, DVC data versioning, PostgreSQL, Docker, background jobs, and CI/CD checks.
Machine learning project evidence
ModelOps Doctor covers monitoring and diagnosis. The evaluation system combines computer vision with assessment workflows. DevMatch AI turns survey data into role predictions and skill-gap guidance.
Assessment platform
Automated Evaluation System
A desktop-style exam workflow for OMR, essays, reports, and review.
Applied machine learning
DevMatch AI
A role predictor and skill-roadmap tool trained on developer-survey data.
Experience beyond the notebook.
At Theta x Tech, I worked on preprocessing pipelines, predictive models, LLM applications, and REST APIs. My computer science studies at Sukkur IBA University focused on AI, machine learning, deep learning, computer vision, and software engineering.
For work centered on agents and business integrations, see my AI automation specialization.
Read my experienceLet's discuss the work.
Share the problem, existing tools, and the result you need. I can discuss implementation scope, technical tradeoffs, and relevant project work.