Machine Learning Engineer

Amir Rahnamai Barghi

Concord, ON, L*K *R* 647-***-**** ********@*****.***

LinkedIn: https://www.linkedin.com/in/amir-rahnama-ph-d-939188229/

Senior Machine Learning Engineer with a strong foundation in mathematics and computer science. Ph.D. in Mathematics and M.Sc. in Computer Science, with over 5 years of hands-on industry experience. Specialized in NLP, transformer-based models (BERT, FinBERT), and deploying scalable ML systems.

Core Competencies

Machine Learning: Proficient in supervised, unsupervised, and deep learning algorithms; expertise in model development and evaluation.

Natural Language Processing: Skilled in text classification, sentiment analysis, language modeling, and semantic similarity using transformer-based models like BERT and FinBERT.

Deep Learning Frameworks: Hands-on experience implementing and fine-tuning models with TensorFlow and PyTorch, including GPU-accelerated training.

Programming: Strong Python development skills with libraries such as NumPy, Pandas, Scikit-learn, PyTorch, and TensorFlow.

Data Preprocessing: Expert in data cleaning, tokenization, stop-word removal, normalization, and preparing structured/unstructured data for ML pipelines.

Model Optimization: Proficient in hyperparameter tuning, model validation strategies, and optimizing trade-offs between accuracy and complexity.

Transfer Learning: Skilled in leveraging and adapting pre-trained transformer models (e.g., BERT) for domain-specific tasks.

Tools & Platforms: Experienced with Jupyter, Git, Azure ML, Google Colab, and various visualization tools (Matplotlib, Seaborn, pyLDAVis).

Data Acquisition & Quality: Capable of supervising data collection, integrating external datasets, and ensuring data quality for training.

Communication & Delivery: Able to translate business objectives into ML solutions and collaborate with cross-functional teams to meet project goals.

Professional Experience

Instructor – Queen’s College of Business and Technology Jan 2024 – Apr 2025

Taught lab-based and Hands-on courses for SQL, NLP for Social Media, Social Media Analysis, Python, Deep Neural Networks, and Machine Learning

Data Scientist – Ernst & Young (EY), Toronto Jul 2022 – May 2023

Developed and fine-tuned BERT/FinBERT models for credit risk prediction

Tuned hyperparameters to balance model complexity and performance

Preprocessed large-scale financial text datasets with tokenization and normalization

Conducted inference optimization and GPU acceleration for production deployment

ML Developer – Justice Canada Jun 2021 – Nov 2021 & Dec. 2020 - Mar. 2021

Built NLP pipelines for classification and semantic similarity using transformer models

Reduced latency via optimized tokenization and simplified preprocessing pipeline

ML Developer – Transport Canada Dec 2019 – Sept 2020

Designed deep learning classifiers for HS code prediction

Preprocessed noisy trade descriptions and normalized text for model accuracy

Focused on trade-offs between model size, accuracy, and runtime efficiency

Data Scientist – Statistics Canada Apr 2019 – Sept 2019

Applied feature engineering and built predictive models using Random Forest algorithm on multi-source retails datasets

Education

Master of Computer Science, University of Ottawa, Ottawa, ON, Canada — September 2015

Ph.D. in Mathematics, TMU University, Tehran, Iran — July 1998

Certifications (Coursera):

Neural Networks and Deep Learning — DeepLearning.AI (Andrew Ng)

Transfer Learning for NLP with TensorFlow Hub — Coursera Project Network

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