Behrooz Azarkhalili
Senior AI Engineer at Novarc Technologies Inc.
Canada
Summary
🤩
Rockstar🎓
Top SchoolBehrooz Azarkhalili is a Senior AI Engineer with seven years of hands-on experience building and deploying ML, DL, and multimodal LLM systems across industry and academia. He combines deep research expertise—from generative models for protein design at UC Berkeley to single-cell variational inference—with production skills in PEFT, quantization, RLHF, and scalable inference on AWS. Comfortable across TensorFlow, PyTorch, JAX and an expansive tooling stack (PEFT, TRL, bitsandbytes, LangChain), he routinely squeezes enterprise-grade performance out of constrained hardware using LoRA/QLoRA and 4–8 bit training. He has taught AI courses, contributed course materials for a Sharif University machine learning curriculum, and led applied teams at startups and research centers, reflecting a rare mix of pedagogy, product delivery, and bioinformatics-driven generative research. Notably, his work bridges NLP, vision, and protein engineering—applying transformer and GNN techniques to real-world scientific problems.
7 years of coding experience
9 years of employment as a software developer
M.Sc., Computer Science, Specialization in Machine Learning, 4.0/4.0, M.Sc., Computer Science, Specialization in Machine Learning, 4.0/4.0 at Georgia Institute of TechnologyM.Sc., Applied Mathematics, 18.42/20.00, M.Sc., Applied Mathematics, 18.42/20.00 at Sharif University of Technology
Github Skills (7)
decision-tree10
machine-learning10
jupyter-notebook9
loss-functions9
artificial-intelligence8
python-course8
ai8
Programming languages (3)
Github contributions (5)
SharifiZarchi/Introduction_to_Machine_Learning
Sep 2022 - Oct 2022
Machine Learning Course, Sharif University of Technology
Role in this project:
ML Engineer
ML EngineerContributions:16 commits, 14 pushes, 1 branch in 1 month
Contributions summary:Behrooz primarily contributed to the course materials related to classical machine learning models. Their commits focused on updating and modifying slides, specifically in the context of decision trees, generalization error, and loss functions. The user's work included adding figures, refining content, and potentially correcting or expanding upon existing material within the slides. They also updated the Jupyter notebooks.
pythonmachine-learningdepartmentengineeringsharif-university
behroozazarkhalili/behroozazarkhalili
Mar 2021 - Apr 2025
Contributions:1 PR, 26100 pushes, 3 branches in 4 years 1 month
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