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The Shipyard: Lessons Learned While Building an ML Platform / Automating Adherence

Posted Apr 07
# ML Platform
# Forecasting and Optimization
# Flexibility
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SPEAKER
Joseph Haaga
Joseph Haaga
Joseph Haaga
Lead MLOps Engineer @ Interos

Joseph leads the ML Platform team at Interos, the operational resilience company. He was introduced to ML Ops while working as a Senior Data Engineer and has spent the past year building a platform for experimentation and serving. He lives in Washington, DC, with his dog Cheese.

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Joseph leads the ML Platform team at Interos, the operational resilience company. He was introduced to ML Ops while working as a Senior Data Engineer and has spent the past year building a platform for experimentation and serving. He lives in Washington, DC, with his dog Cheese.

+ Read More
SUMMARY

Joseph Haaga and the Interos team walk us through their design decisions in building an internal data platform. Joseph talks about why their use case wasn't a fit for off the self solutions, what their internal tool snitch does, and how they use git as a model registry. Shipyard blogpost series: https://medium.com/interos-engineering.

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