How to Write an Impressive Machine Learning Engineer Resume

Getting that dream job as a Machine Learning Engineer involves more than writing good code and building effective machine learning models. To stand out in the field of candidates who are trying to break into the competitive AI space, you’ll need an exceptional technical resume. Here’s a breakdown of what you’ll want to include in your Machine Learning Engineer resume to get a hiring manager’s attention.

What to include in a Machine Learning Engineer resume 

Here are the main sections your machine learning resume should have, starting at the top: 

Contact information 

Recruiters can’t contact you unless you give them a way to, so your contact information should be easy to find and read. Put it directly under your name at the top of the resume or in the top right corner. Include your name, phone number, and email address. You can also include a link to your portfolio website and (optimized) LinkedIn profile. 

Also, use a professional email address — one that has your name or some variation of it. 

Summary 

Some people include summaries in their resume, others don’t. They’re not required, but you can use them to add context to your story and the accompanying info. Your summary is a brief (think one to two sentences) statement about who you are and what you do that you can include right after your contact info. You can also succinctly mention the job you’re applying for, the skills you have that make you a good fit, and what you would like to accomplish with the role. 

Need some help writing? Here are easy tips for writing a concise professional bio, plus a few examples. Another helpful hint: Some people find it easier to write their summary last, after they’ve filled out and completed their resume.  

Programming skills 

Here are some skills you may need in a machine learning role: 

• Model development 
• Data mining 
• Predictive analytics 
• Clustering and classification
• Web scraping 
• Statistical modeling 
• Data visualization 

These are the programming languages that are typically used for machine learning: 

• Python 
• R 
• Java 
• JavaScript 
• C++ 
• Shell 
• Go 

Along with general machine learning skills and languages, list specific tools you use, like TensorFlow, Keras, or scikit-learn, and any skills that are listed as “required” in the job posting. Need to brush up on some of these key machine learning tools? Check out our catalog of machine learning courses to fill in your skill gaps.  

It’s important to look at the job description you are applying to when you list your skills because the role may have more responsibilities than building machine learning models. Some may require that you have other skills like back-end development if the job requires you to build a machine learning pipeline or front-end development if the job includes data visualization tasks. 

Experience and work history 

In this section, list your work experience in reverse chronological order. Start with your most recent job and work your way back in time. Each listing should have: 

• Your job title 
• The company you worked for 
• The city and state the company is located 
• A description of what you did at the job 

For each description, highlight how you contributed to company goals. If you’re tailoring this resume to a specific job, emphasize responsibilities you’ve had that are similar to those listed. Even if your previous roles weren’t in tech, there are lots of transferrable soft skills that can make you stand out as a candidate.  

First-time job seekers or career switchers may not have a ton of work experience to list. But keep in mind that you can highlight any courses, projects, or experiences that are relevant to the role you’re applying to.  

Education and courses 

This section will use reverse chronological order again to list the colleges and schools you attended and the courses you took. If any of this education resulted in a degree or certificate, make sure to mention that. 

If you haven’t been to college, don’t worry — list the online courses and paths you’ve taken, including our machine learning courses. If you earned one of our professional certificates for completing a path, be sure to list it. Hiring managers just need to know you have the skills and dedication to do the job, and a degree isn’t necessary for many roles. Read this blog for more tips on how to get in the door without a formal degree. 

How to make sure your Machine Learning resume gets noticed 

As more companies and recruiters utilize AI tools to review resumes, it’s important to tactically format and word your resume. The tips below will help your resume get past scanners and boost your chance of landing an interview: 

• Customize each resume: It’s a good plan to have more than one resume. Keep one as your template and create a new custom resume for each job. Each role you apply to will have different job requirements and responsibilities. Customizing your resume based on the job descriptions gives you a chance to emphasize your skills that fit the employer’s needs. (You can even use ChatGPT to tailor your resume for different roles.) 
• Save it as a PDF: Unless the posting says otherwise, the best format for your resume is PDF. Keep the original in Word or whatever format you prefer so you can edit it, but the PDF format guarantees your resume will look the same on any device. 
• Use action verbs in your work experience: Use words like “led,” “created,” “developed,” and “wrote” when you describe what you accomplished in each past role to show employers what you can do. 
• Format it well: The right formatting can make your resume stand out and easier to read. Make sure the fonts you use are readable, and use columns, if you can, to use the space you have effectively. You can find many free templates and examples online. 

How to prepare for your Machine Learning Engineer interview 

Once you’ve polished your resume with the tips listed here and submitted it to hiring managers and recruiters, you have completed the first step towards landing your dream Machine Learning Engineer job. Next, you should build a machine learning portfolio and prepare for your interview. 

Check out our blog to pick up tips for taking the technical and behavioral interview. We also have blogs that will help you prepare specifically for answering machine learning interview questions. And if you need a refresher, check out our Learn the Basics of Machine Learning course or our career path Machine Learning/AI Engineer.