Applying for Machine Role jobs? This summary of 200+ resumes has sincere advice

I just went through 200+ applications for a machine learning position. I think I figured out what works and doesn’t in a resume. Here are a few tips.
The question I want to answer when I read a resume: • Should I call this person? Anything that doesn’t help me with this decision is working against you.
The most common problem I found when reviewing applications: Most resumes are 90% noise and 10% signal. People bury relevant details in an ocean of useless information. Fix this, and you increase your chances significantly.
How can you make your resume 100% on point? 1. Keep your resume down to one page. 2. Tailor your resume to the position. 3. Remove anything that doesn’t speak to the job. Let’s break these down.
1. Keep your resume down to one page Nobody ever looks at the second page of their Google search. The same happens with your resume. If I’m not sold after reading the first page, nothing will change my mind on the second page.
2. Tailor your resume to the position. Are you applying for a computer vision position? Center your resume around that. Don’t let the person reading the resume hunt for clues. Everything relevant should be right there on their face.
3. Remove anything that doesn’t speak to the job. The resume is not the place to list your life accomplishments unless they contribute to getting that call. Connect every line you write to the job opening. If you can’t, get rid of it.
With every resume, I found myself looking for a quick way to decide whether the person was a good fit. A 2-3 sentence summary is your opportunity to shine. Your sales pitch right at the top: • What are you looking for? • What are you capable of? • Why are you good at it?
Your education is important. But in my opinion, your experience is the most valuable asset you bring to the table. Experience > Education Don’t start with your certifications, diplomas, and degrees. Start with what you have done and how it is relevant to the job.
Speaking about education: Keep superfluous details out of your resume. It only adds to the noise, and nobody cares: • Your GPA • Your coursework at school • Anything that happened 10+ years ago
Many people don’t read the job post. Popular advice: “Apply if you meet half the requirements.” I disagree. If the requirements are stupid, don’t apply at all. If they make sense, but you don’t meet them, don’t apply either. Spend your time on battles that you can win.
I want to make an exception with job posts that clearly ask for impossible requirements. Those who ask for 10 years of experience in a framework that’s 5 years old. Most people laugh at these. I think they are an incredible opportunity.
Companies that need a lot of help and are just creating their teams don’t know better. They’ll copy requirements from here and there and put together a half-assed job post. If you get this job, you’ll start from the ground floor. You’ll get to build a team from scratch!
Getting back at people not reading job posts: The post asks for people with experience in ABC technology. Yet you mention ABC as your 9th bullet right after 8 completely irrelevant points. I discard those resumes pretty quickly: they are clearly mass-applying to jobs.
Is mass-applying to jobs a problem? Not really. But if you do, you won’t be able to compete with a resume that’s speaking directly to the position. In my book: Quality > Quantity (But I understand this looks different at different stages of your career.)
To recap: • Your goal: Getting a call • Read the job post • Tailor your resume • Cut it down to 1 page • Sale yourself in 2-3 sentences • Experience > Education • No superfluous details • Quality > Quantity
I post threads like this every week. More than once. Stay tuned as I help you get to the core of practical machine learning. You can find the rest of my threads here: @svpino.

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