Summary
Mina Parham is a Machine Learning Engineer with 8 years of professional experience and 4+ years focused on AI research and engineering, specializing in LLMs, reinforcement learning, and scalable deep learning systems. She has moved seamlessly between research roles at Université de Montréal and hands-on engineering at startups and enterprises, driving practical gains like a 2.2x inference speedup and memory-efficient fine-tuning using LoRA, QLoRA, and double quantization. Mina teaches and distills complex topics — authoring a DataCamp course on RLHF — and has implemented PPO-based RLHF pipelines in production, reflecting her blend of pedagogy and engineering. Comfortable leading refactors and system design, she’s improved inference availability with async endpoints and cost-saving automation, showing pragmatic efficiency alongside model improvements. Energized by ambiguity, she gravitates toward alignment tuning and generative-AI problems, preferring to fall in love with the problem rather than a particular solution. Based in Toronto, Mina combines strong academic foundations with a track record of shipping impactful ML products and tooling.
8 years of coding experience
6 years of employment as a software developer
Amirkabir University of Technology
Master's degree, AI - Polytechnique Montréal, Master's degree, AI - Polytechnique Montréal at Université de Montréal
English