June 2, 2022, 11:43 p.m. | Chip Huyen, Shijing Fang, Vernon Germano

InfoQ - AI, ML & Data Engineering www.infoq.com

The panelists discuss lessons learned with putting ML systems into production, what is working and what is not working, building ML teams, dealing with large datasets, governance and ethics/privacy.

By Chip Huyen, Shijing Fang, Vernon Germano

ai devops machine learning ml ml & data engineering panel presentation production qcon plus november 2021 transcripts virtual panel

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Senior Machine Learning Engineer (MLOps)

@ Promaton | Remote, Europe

Healthcare Data Modeler/Data Architect - REMOTE

@ Perficient | United States

Data Analyst – Sustainability, Green IT

@ H&M Group | Stockholm, Sweden

RWE Data Analyst

@ Sanofi | Hyderabad

Machine Learning Engineer

@ JPMorgan Chase & Co. | Jersey City, NJ, United States