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ML Engineers these days

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Manage episode 426490875 series 2805538
Content provided by mnemonic. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by mnemonic or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Have you ever worked alongside a machine learning engineer? Or wondered how their world will overlap with ours in the "AI" era?

In this episode of the podcast, Robby is joined by seasoned expert Kyle Gallatin from Handshake to enlighten us on his perspective on how collaboration between security professionals and ML practitioners should look in the future. They discuss the typical workflow of an ML engineer, the risks associated with open-source models and machine learning experimentation, and the potential role of "security champions" within ML teams. Kyle provides insight into what has worked best for him and his teams over the years, and provides practical advice for companies aiming to enhance their AI security practices.

Looking back at our experience with "DevSecOps" - what can we learn from and improve for the next iteration of development in the AI era?

  continue reading

Chapters

1. Security in AI and Machine Learning (00:00:00)

2. Model Registry and Security in ML (00:09:40)

3. Empathy in ML and Security Collaboration (00:17:35)

119 episodes

Artwork
iconShare
 
Manage episode 426490875 series 2805538
Content provided by mnemonic. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by mnemonic or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Have you ever worked alongside a machine learning engineer? Or wondered how their world will overlap with ours in the "AI" era?

In this episode of the podcast, Robby is joined by seasoned expert Kyle Gallatin from Handshake to enlighten us on his perspective on how collaboration between security professionals and ML practitioners should look in the future. They discuss the typical workflow of an ML engineer, the risks associated with open-source models and machine learning experimentation, and the potential role of "security champions" within ML teams. Kyle provides insight into what has worked best for him and his teams over the years, and provides practical advice for companies aiming to enhance their AI security practices.

Looking back at our experience with "DevSecOps" - what can we learn from and improve for the next iteration of development in the AI era?

  continue reading

Chapters

1. Security in AI and Machine Learning (00:00:00)

2. Model Registry and Security in ML (00:09:40)

3. Empathy in ML and Security Collaboration (00:17:35)

119 episodes

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