Muhammad Dawood Khan
Building ML systems that ship to production — not just notebooks.
About
Muhammad Dawood Khan is an MLOps and Machine Learning Engineer building and deploying production-grade ML systems. From experiment tracking with MLflow and DVC to containerized deployments on Railway, his work spans the full ML lifecycle.
He has shipped a live property valuation API, contributed ML models to PhD-level AI labor economics research, and built medical imaging pipelines achieving 0.92 Dice score. He specializes in making models production-ready — not just accurate.
Core Competencies
MLOps & Deployment
ML/DL Frameworks
Languages & Infra
Data Engineering
Shipped Work
propval-pk
Pakistan Property Valuation API. End-to-end MLOps pipeline for real estate price prediction. Integrates Bayesian target encoding and quantile regression for uncertainty-aware predictions.
Brain Tumor Segmentation
Medical Imaging pipeline. Implements 2D MRI segmentation using a customized ResNet-34 semantic segmentation model with specialized data augmentations and mixed-precision training.
textile-scheduler
Production Web App. A full-stack monorepo, end-to-end deployed, solving CORS, containerized caching and builds, and establishing a robust production release pipeline.
SOFTEC 2025 ML Competition
Ensemble Pipeline for predictive ML. Engineered a six-model ensemble framework with automated Optuna hyperparameter sweeps and integrated TabNet/CatBoost estimators.
PhD Thesis Collaboration
AI Labor Economics. Led machine learning and statistical modeling (Random Forest & Logistic Regression) to analyze the impact of AI adoption on twin cities' IT labor market.
Image Classification Pipeline
Delivered a highly reproducible image classification pipeline fine-tuning ResNet models on STL-10, with automated evaluation reporting and structured hydra configuration management.
Experience
PhD Thesis Collaboration (ML & Econometrics)
2025 – PresentExecuting machine learning and econometric modeling (Random Forest, Logistic Regression, K-Means Clustering) on survey data from IT firms to analyze labor market dynamics, reskilling needs, and job displacement risks.
Freelance Machine Learning Engineer
2024 – PresentContracted by diverse clients to design and deploy specialized ML models. Delivered scalable image classification tools, engineered reproducible pipelines using configuration frameworks, and implemented automated performance logging systems.
Let's Build Something
Open to MLOps, ML Engineering, and Data Science opportunities. Based in Pakistan, available remotely. Let's design something scalable.