Building Scalable ML Infrastructure at Outerbounds with Savin Goyal

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

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Shuai Wang’s Journey from China to Charleston 38:30

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Chef Shuai Wang was the runner-up on the 22nd season of Bravo’s Top Chef and is the force behind two standout restaurants in Charleston, South Carolina—Jackrabbit Filly and King BBQ—where he brings together the flavors of his childhood in Beijing and the spirit of the South in some pretty unforgettable ways. He grew up just a short walk from Tiananmen Square, in a tiny home with no electricity or running water, where his grandmother often cooked over charcoal. Later, in Queens, New York, his mom taught herself to cook—her first dishes were a little salty, but they were always made with love. And somewhere along the way, Shuai learned that cooking wasn’t just about food—it was about taking care of people. After years working in New York kitchens, he made his way to Charleston and started building something that feels entirely his own. Today, we’re talking about how all those experiences come together on the plate, the family stories behind his cooking, and what it’s been like to share that journey on national TV. For more info visit: southernliving.com/biscuitsandjam Learn more about your ad choices. Visit podcastchoices.com/adchoices…

vor etwa einem Jahr 36:46

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Key Takeaways:

(02:02) Savin spent years building AI and ML infrastructure, including at Netflix.

(04:05) ML engineering was not a defined role a decade ago.

(08:17) Modernizing AI and ML requires balancing new tools with existing strengths.

(10:28) ML workloads can be long-running or require heavy computation.

(15:29) Different teams at Netflix used multiple orchestration systems for specific needs.

(20:10) Stable APIs prevent rework and keep projects moving.

(21:07) Metaflow simplifies ML workflows by optimizing data and compute interactions.

(25:53) Limited local computing power makes running ML workloads challenging.

(27:43) Airflow UI monitors pipelines, while Metaflow UI gives ML insights.

(33:13) The most successful data professionals focus on business impact, not just technology.

Resources Mentioned:

Savin Goyal -

https://www.linkedin.com/in/savingoyal/

Outerbounds -

https://www.linkedin.com/company/outerbounds/

Apache Airflow -

https://airflow.apache.org/

Metaflow -

https://metaflow.org/

Netflix’s Maestro Orchestration System -

https://netflixtechblog.com/maestro-netflixs-workflow-orchestrator-ee13a06f9c78?gi=8e6a067a92e9#:~:text=Maestro%20is%20a%20fully%20managed,data%20between%20different%20storages%2C%20etc.

TensorFlow -

https://www.tensorflow.org/

PyTorch -

https://pytorch.org/

Thanks for listening to “The Data Flowcast: Mastering Airflow for Data Engineering & AI.” If you enjoyed this episode, please leave a 5-star review to help get the word out about the show. And be sure to subscribe so you never miss any of the insightful conversations.

#AI #Automation #Airflow #MachineLearning

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Building Scalable ML Infrastructure at Outerbounds with Savin Goyal

The Data Flowcast: Mastering Apache Airflow ® for Data Engineering and AI

38 subscribers

published vor etwa einem Jahr