---
title: "Optimize AI at Scale With Platform Engineering for MLOps"
url: https://daily.dev/posts/optimize-ai-at-scale-with-platform-engineering-for-mlops-cls0dtd0f
source_url: https://thenewstack.io/optimize-ai-at-scale-with-platform-engineering-for-mlops/
type: article
source: "The New Stack"
published: 2024-05-09T17:11:02.520Z
updated: 2024-05-09T17:11:01.779Z
tags: ["ai", "machine-learning", "devops", "mlops", "platform-engineering"]
reading_time: 5
upvotes: 0
comments: 0
language: en
---

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# Optimize AI at Scale With Platform Engineering for MLOps

**[The New Stack](https://daily.dev/sources/newstack)** · 5 min read · 0 upvotes · 0 comments

## Summary

AI adoption is increasing in enterprises and optimizing MLOps at scale is crucial for delivering positive ROI. Platform engineering can streamline MLOps workflows by recognizing the differences between DevOps and MLOps and implementing purpose-built solutions. Distributed enterprises can scale AI by utilizing a customizable spoke-and-wheel approach. A purpose-built platform engineering solution must address infrastructure optimization, model management and deployment, data governance and privacy, model observability, and task automation and self-service. Future-proofing the platform engineering solution involves managing it as a product, hiring engineers with MLOps experience, and staying adaptable to new technologies.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://thenewstack.io/optimize-ai-at-scale-with-platform-engineering-for-mlops/>

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---

Tags: [#ai](https://daily.dev/tags/ai), [#machine-learning](https://daily.dev/tags/machine-learning), [#devops](https://daily.dev/tags/devops), [#mlops](https://daily.dev/tags/mlops), [#platform-engineering](https://daily.dev/tags/platform-engineering)

[View this post on daily.dev](https://daily.dev/posts/optimize-ai-at-scale-with-platform-engineering-for-mlops-cls0dtd0f)