Dave Burgess
Head of Data Engineering, Pinterest. On 1 show, 1 appearance. The Shows tab opens the full record on each.
1shows
1appearances
14statements
2resolved
1supported
1contradicted
50%fully supported
Everything Dave Burgess said on any show that made the record, most notable first. Each card names its show and opens the statement there.
Pinterest visual search beats Google and Bing in head-to-head tests
“You'll find that Pinterest is usually the one that comes out of top.”
Apache Kafka was built on prior engineering work at Yahoo
“Things like Kafka eventually came out of LinkedIn that was based on work that we had been doing at Yahoo”
Pinterest manages open-source data tech in-house to limit downtime
“Yeah, we do. I mean, we're fortunate to have the number of engineers to do that, and one of the reasons why we work directly either with the open source community or the companies that are also working on that is that we want Pinterest to be up all the time, a…”
Pinterest embeds machine learning engineers directly within product teams
“With machine learning is actually distributed everywhere. We have Many, many machine learning engineers and many, many use cases. And those mission machine learning engineers are embedded within each organization.”
Pinterest wants non-coding data scientists to deploy ML models to production
“And to get to a point where we can have people that are data scientists that don't even code, that can just build models and be able to deploy those to production. So that's really what we want to get to within Pinterest as well.”
Yahoo used ML and behavioral targeting in ads over 15 years ago
“We were doing machine learning and behavioral targeting back 15 years ago, more than 15 years ago in advertising.”
Pinterest runs about 1,000 parallel A/B experiments at any time
“And so we have about a thousand experiments running in parallel at any point of time.”
Pinterest deploys machine learning across roughly 80 distinct use cases
“So we have about 80 different use cases of machine learning.”
Pinterest platform deploys ML models across thousands of servers within hours
“So we, what we can do is within a few hours, you could do create a model, train a model, and then deploy it to our production service with thousands and thousands of servers by using this MLflow repository.”
Pinterest uses 50 machine learning models in its pin safety pipeline
“And so, there's a, that whole pipeline has got like about 50 different machine learning models in itself.”
Pinterest reduced maintenance costs, latency, and infrastructure expenses by migrating to Druid
“And so we decided to migrate that to Druid. And so the maintenance cost has gone way down. The latency has gone way down. The actual cost of running the infrastructure way down. So really, really happy.”
Pinterest operates over 2,000 production workflows on Apache Airflow
“We're still using the APIs for the existing system so that we could migrate, but we have over 2000 workflows running in production.”
Burgess outlines Pinterest's online serving and batch data engineering stack
“So data engineering at Pinterest comprises the serving part, all the online systems. So that includes the online databases like MySQL and key value stores like RocksDB and HBase, and also includes Druid platform. So we have our online systems. We also have all…”
One line per show, most statements first. The link opens Dave's full record on that show: the calibration, argument clarity, speaking style and every statement made there.
| Show | Role there | Eps | Statements | Record | |
|---|---|---|---|---|---|
 MADLEDGER | Head of Data Engineering, Pinterest | 1 | 14 | 50% 1/2 | full record on the MAD Podcast → |