Evolving the ML Platform organisation at Netflix: a case study
YOW! Data 2021
Do you wish there was a Machine Learning model to tell you how to structure your ML teams? So do I! While we're waiting for that, I'll share the story of how the ML Platform organisation evolved at Netflix. Although this story is specific to our own journey to expand Netflix ML investments, there are a few lessons learned along the way that you'll be able to relate to. There are several factors going into org structure that we'll discuss, including: the specialty and skillsets of ML practitioners, the variety and depth of ML use cases, who's responsible for the data, the ownership model as ML projects go to production, and how the underlying Platforms are situated. I look forward to sharing and hearing your own thoughts afterward!
Director, Machine Learning Platform
Julie Amundson is Director of Machine Learning Platform Experience at Netflix, with the mission of providing a productive, innovative and dependable experience for ML practitioners across the company. In the early days of Netflix streaming, she worked on infrastructure behind the "play" button as Netflix was expanding to stream on all internet-connected devices and becoming available across the world.
Julie also co-founded Order of Magnitude Labs, aiming to build AI capable of endeavors that humans find easy and today’s machines find hard: exploration, communication, creativity and accomplishing long-range goals. Early in her career, Julie developed data processing software at Lawrence Livermore National Laboratory that enabled scientists to study the newly-sequenced human genome.