Source URL: https://www.tomtunguz.com/netflix-new-ai-role/
Source: Tomasz Tunguz
Title: Netflix’s New AI Role
Feedly Summary: Netflix invented a new role for their data team : the Media ML Data Engineer.
Unstructured data is fundamentally different. It’s multimodal & contains derived fields like embeddings, captions, & transcriptions. It’s also at least 80% of the world’s data & essential for the field of AI.
This new role highlights how one of the most important companies within the data ecosystem has evolved to promote multimodal data as core. Software engineering & data engineering are fusing.
Netflix’s Team Multimodal Architecture
Different data producers send their data to a media machine learning data engineer who then supplies it for analytics, data science, & applied AI.
At the core of this role is a technology : the media data lake. In addition to access, metadata management, & data preparation, the new media data lake becomes an essential component of AI. Powering all of this is a portfolio company LanceDB.
We wrote about this type of architecture in 2022 in 9 Predictions for Data in 2023 & it’s thrilling to see it come to life at Netflix.
The demand for engineers who understand both traditional data infrastructure & multimodal AI will only grow.
Companies like LanceDB are building the next generation of data platforms to support this evolution. If you’re ready to work at this intersection, check out their open positions.
AI Summary and Description: Yes
Summary: The text discusses the introduction of a new role at Netflix, the Media ML Data Engineer, which reflects the evolving landscape of data engineering and AI. This role is focused on managing unstructured multimodal data, highlighting the importance of such data in AI applications.
Detailed Description:
The introduction of the Media ML Data Engineer at Netflix signals a significant shift in how organizations approach data engineering, particularly as it pertains to AI. The role is essential in handling unstructured data—which comprises a substantial portion of global data—and emphasizes the integration of various forms of data such as embeddings, captions, and transcriptions.
Key Points:
– **Role Definition**:
– The Media ML Data Engineer is tasked with managing multimodal data produced by different sources.
– This role facilitates analytics, data science, and applied AI efforts within Netflix.
– **Data Infrastructure**:
– The role leverages a technology known as the media data lake.
– The media data lake is crucial for access, metadata management, and data preparation, becoming instrumental for AI functionalities.
– **Industry Trends**:
– The text implies that as technology evolves, the convergence of software engineering and data engineering is becoming foundational to the AI landscape.
– There is a growing demand for professionals skilled in both traditional data infrastructures and multimodal AI techniques.
– **Company Insights**:
– Companies like LanceDB are leading the charge in creating innovative data platforms to support these emerging needs in data architecture.
– The evolution of roles like the Media ML Data Engineer showcases how businesses are adapting to changes in data dynamics.
This development is particularly significant for professionals involved in cloud computing, AI security, and data management, as it highlights the importance of integrating innovation within data roles to stay relevant in a rapidly evolving technological environment. The call to action for candidates to explore opportunities in this field suggests a burgeoning job market for talent at the intersection of data science and AI.