Data Engineering Entertainment Infrastructure 
The Netflix TechBlog
NOVEMBER 22, 2019
Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Instead, we provide them with delightfully usable ML infrastructure that they can use to manage a project’s lifecycle. Wednesday?—?December
The Netflix TechBlog
MARCH 7, 2024
Berg , Romain Cledat , Kayla Seeley , Shashank Srikanth , Chaoying Wang , Darin Yu Netflix uses data science and machine learning across all facets of the company, powering a wide range of business applications from our internal infrastructure and content demand modeling to media understanding.
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The Netflix TechBlog
JANUARY 11, 2022
To learn about Analytics and Viz Engineering, have a look at Analytics at Netflix: Who We Are and What We Do by Molly Jackman & Meghana Reddy and How Our Paths Brought Us to Data and Netflix by Julie Beckley & Chris Pham. Curious to learn about what it’s like to be a Data Engineer at Netflix?
The Netflix TechBlog
NOVEMBER 22, 2019
Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Instead, we provide them with delightfully usable ML infrastructure that they can use to manage a project’s lifecycle. Wednesday?—?December
The Netflix TechBlog
NOVEMBER 22, 2019
Netflix shares how Amazon EC2 Auto Scaling allows its infrastructure to automatically adapt to changing traffic patterns in order to keep its audience entertained and its costs on target. Instead, we provide them with delightfully usable ML infrastructure that they can use to manage a project’s lifecycle. Wednesday?—?December
The Netflix TechBlog
MARCH 2, 2021
At Netflix, our data scientists span many areas of technical specialization, including experimentation, causal inference, machine learning, NLP, modeling, and optimization. Together with data analytics and data engineering, we comprise the larger, centralized Data Science and Engineering group.
All Things Distributed
NOVEMBER 15, 2016
As I mentioned, we live in a world where massive volumes of data are being generated, every day, from connected devices, websites, mobile apps, and customer applications running on top of AWS infrastructure. Put simply, data is not always readily available and accessible to organizational end users.
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