AI needs great engineers.

The real difficulty when it comes to real-world AI isn’t modeling—it’s finding a way to run those models in production. This is a feat that requires a ton of engineering.

I work on machine learning infrastructure at Google and see the complexities of this engineering every day. We train massive models and then serve them to billions of users. Machine learning systems take classic software engineering problems and 10x their scale. If you like software engineering, you will love building ML systems.

I write Machine Learning for Software Engineers to help software engineers understand their role in a world with AI and get them up-to-speed on machine learning so they can be a part of it. There is unprecedented demand for software engineers within AI and you likely already have the skills needed.

Subscribe now to get 2 or 3 emails in your inbox each week to help you up-skill in AI.

Need further convincing?

Here’s what subscribers say about Machine Learning for Software Engineers:

• “Logan is a long-time ML engineer that does an awesome job of explaining the intersection of ML/engineering (and beyond) in a digestible manner.” -

  Cameron R. Wolfe, Ph.D.
  ,
  Deep (Learning) Focus

• “Logan from [Machine Learning for Software Engineers] is doing an amazing job demystifying machine learning!” -

  Sahar Mor
  ,
  AI Tidbits

• “I never miss an issue. A great source of information, tools and updates.” -

  Riccardo Vocca
  ,
  The Intelligent Friend

• “A solid mix of AI news and ML engineering insights, written by an ML engineer at Google.” -

  MLOps Community

• “Some of the most insightful AI perspectives and technical expertise from a prominent Google data scientist. (Though the Spider-Man shirt? Still on the fence about that one. 🤷)” -

  Sergei Polevikov
  ,
  AI Health Uncut

And more:

Articles to get started

If you’re unsure about joining, check out some of my favorite articles:

• How AI systems don’t conform to the traditional software engineering practices

• AI coding assistants exposing software engineers

• Why machine learning infra is so cool

• A simple way to understand machine learning

and many other topics.

Other resources

I’ve also written a streamlined road map to learn ML fundamentals for free.

If newsletters aren’t your thing, I totally understand! You can also treat Machine Learning for Software Engineers as a blog and find me on your favorite social platform:

• YouTube

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• LinkedIn

We also have a community Chat here on Substack for subscribers.

Never hesitate to reach out. I’d love to chat. 😊

Always be (machine) learning,

Logan