A question I get asked all the time is what to do if you don’t have a degree but you want to work in AI/ML.

Should you go for a Master’s? Is there a way around it? Is it even realistic to pursue this field without the qualifications on job descriptions?

This video breaks it down. I go over what the requirements from employers are, and how to get around them if you don’t necessarily check every box.

Blog version is here.

I’m planning future content and partnerships, and I’d love to learn more about your interests, both for your career development and outside of that.

This survey should take about five minutes. Your answers will help me choose topics, products, and brand partners that are more relevant and helpful to you.

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When most folks prepare for interviews, they focus on the technical part: coding, system design, all that good stuff.

But there’s one question that’s more important than all the rest, and most people don’t bother preparing for it at all:

“Tell me about yourself.”

Sounds simple, right?

Yeah…but it’s also simple to mess up. And flubbing here can be ruinous for the rest of your interview. I can’t tell you how many times I’ve been interviewing someone, and they go on a 10 minute monologue that doesn’t help sell their fit for the role at all. At the end of that, I’m usually 90% decided on whether or not I’ll suggest hiring them, even if the rest of the interview goes flawlessly.

This is actually a really simple question to answer. I suggest this format:

Keep the whole pitch short, like 1-2 minutes, and make it as targeted to the role you’re interviewing for as possible.

For example, let’s say I’m interviewing for a role on an ML team that does recommendations. I might say:

I’m currently a Senior Applied Scientist at Twitch where I’ve spent the last four years building production ML systems with a focus on Gen AI and ML infrastructure. Last quarter I delivered a content understanding project that improved the view-to-follow rate our clips feed by 1.5%.

Prior to Twitch I spent two years as an ML Scientist at Coursera, where I migrated the legacy course recommendations model to a deep learning approach.

Now I’m looking for a role on a team where I can get more experience with real-time recommendations systems and continue building on my Gen AI skills, and this role caught my attention because your team is working on exactly the intersection of serving recommendations at scale in a low-latency environment, and from the job description it sounds like you're actively exploring how LLMs fit into that stack. I'd get to apply what I've built at Twitch while growing in the direction I want, and I think my experience shipping Gen AI features in a high-traffic production environment would let me contribute quickly.

Hope this is helpful!

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