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@mubeenbutt2
AI/ML engineer and data scientist delivering production-ready deep learning and MLOps solutions.
I am an AI/ML engineer and data scientist with over 9 years of experience building scalable machine learning solutions across fintech, healthcare, and logistics.
I design predictive models and deep learning architectures and deploy production-ready systems using Python, TensorFlow, PyTorch, XGBoost, and AWS SageMaker, focusing on measurable business impact.
I have led teams, standardized MLOps pipelines with MLflow, Airflow, Docker, and implemented CI/CD, model monitoring, and explainability (SHAP, LIME) to meet regulatory and operational requirements.
Key achievements include reducing inventory stockouts by 22% with forecasting systems, achieving 92% sensitivity on diabetic retinopathy models, and improving fraud capture by 45% through real-time detection pipelines.
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Work history, roles, and key accomplishments
Forecast Flow
Apr 2022 - Present (3 years 7 months)
Architected and led deployment of cloud-native ML forecasting systems for enterprise supply chain and retail, reducing inventory stockouts by 22% and standardizing reproducible MLOps pipelines.
Clarity
Jan 2019 - Feb 2022 (3 years 1 month)
Led development of deep learning pipelines for OCT medical image disease detection achieving 92% sensitivity and optimized edge deployments with ONNX/TensorRT for real-time clinical inference.
mpsWORKS
May 2016 - Dec 2018 (2 years 7 months)
Engineered fraud detection and credit scoring models using XGBoost and logistic regression, increasing precision by 17% and deploying low-latency risk pipelines integrated with transactional APIs.
Degrees, certifications, and relevant coursework
Bachelor of Science, Computer Science
2011 - 2015
Bachelor of Science in Computer Science completed from 2011 to 2015.
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