Mohammad Akbari

Machine Learning Engineer @Upwork

Toronto, ON, CA

Designed and deployed end-to-end machine learning models for fraud detection, leveraging anomaly detection, classification algorithms, and real-time scoring pipelines to reduce false positives by 30%.• Developed personalization algorithms using collaborative filtering and deep learning techniques, driving a 20% increase in user engagement through tailored recommendations.• Conducted data analysis and feature engineering on large-scale behavioral and transactional datasets to extract actionable insights, improving model accuracy across multiple business domains.• Built and optimized marketplace optimization models to balance supply-demand dynamics, applying regression, reinforcement learning, and constrained optimization, resulting in a 15% uplift in market efficiency.• Implemented scalable ML pipelines using tools like Python, TensorFlow, PyTorch, and Spark, ensuring robust model training, validation, and deployment in production environments.• Collaborated with cross-functional teams to deploy models into production, integrating with APIs and monitoring systems for continuous performance tracking and improvement.• Utilized A/B testing and statistical analysis to evaluate model impact, driving data-driven decisions and iterative enhancements to machine learning solutions.• Automated model retraining workflows using MLOps best practices, including CI/CD pipelines, version control, and performance monitoring, ensuring reliability and scalability.

Isfahan University of Technology

Bachelor of Applied Science (B.A.Sc.), Mechanical Engineering

Queen's University

Doctor of Philosophy - PhD, Applied Mathematics - Machine Learning & Control Theory

Isfahan University of Technology

Bachelor of Science (B.Sc.), Mathematics

Queen's University

Master's degree, Applied Mathematics - Optimization & Distributed Systems