Amir Raza is an Applied Scientist II with 8 years of hands-on experience building and deploying ML solutions across cybersecurity, healthcare, education, and recommendation systems. He combines deep learning and NLP expertise—having designed self-supervised fine-tuning for BERT and worked on reviewer recommendation at Mila—with practical production experience using lightweight models like Random Forest and Isolation Forest for malware and phishing detection. At Amazon and prior roles he has bridged research and engineering to take models from prototype to product, including LLM work for healthcare and probabilistic student modeling for adaptive tutoring. A featured speaker at the Toronto AI Conference on ML in cybersecurity, he brings uncommon breadth across research-grade transformer methods and resource-efficient applied systems. Based in Montreal and fluent in cross-domain problem framing, he’s also an avid language learner, reflecting a continuous curiosity that fuels both his research and product work.
8 years of coding experience
6 years of employment as a software developer
Masters, Masters at Mila - Quebec Artificial Intelligence Institute
Master's degree Computer Science, Master's degree Computer Science at Université de Montréal
Contributions:56 pushes, 1 branch in 4 years 9 months
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