Summary
Nate Lee is a Senior Consultant and Machine Learning Engineer with eight years of experience designing and shipping AI/ML pipelines, MLOps platforms, and edge-deployed computer vision systems. He has led end-to-end data-centric AI efforts at Dyson and built production recommender and marketing automation systems at Sephora, plus a RAG-based GenAI chatbot for Visa’s ops team. Comfortable across Python, C++, Go and cloud-native tooling (AWS, SageMaker, Terraform), he bridges research-grade deep learning (TensorFlow, PyTorch, Core ML) with pragmatic deployment on iOS and edge IPUs. Nate combines product-minded engineering—saving six-figure budgets and delivering measurable marketing revenue—with hands-on MLOps expertise (Airflow, MLflow, dbt, CI/CD). Based in Singapore, he balances a disciplined technical career with curiosity-driven learning and family life, and publishes technical articles and code on GitHub and Towards Data Science.
8 years of coding experience
8 years of employment as a software developer
Master of Science Computer Science, Master of Science Computer Science at Georgia Institute of Technology
Master of IT in Business Artificial Intelligence, Master of IT in Business Artificial Intelligence at Singapore Management University
Lomonosov Moscow State University
Chinese, English, Russian, teochew