Bridging the gap between Machine Learning and Engineering
Machine learning is leaving the lab and hitting production.
Making this transition successfully requires significant engineering expertise -
from new pipelines and infra, to development methodologies, to operational practices and more.
I’ve built and helped others build many successful machine learning systems, teams and processes to address these challenges - whether massive scale data or moderate scale, Classical ML or Deep Learning, Fortune 500 or tiny organizations.
