Machine Learning Resume Examples [Also for an Engineer]

You’re no stranger to sorting and filtering data on an inhuman scale. Finding meaningful patterns and useful correlations in tangled masses of information. Somewhere, a human recruiter will be sorting through machine learning resumes, filtering and eliminating and then comparing and assessing.

Just like preparing a data set, prepare your machine learning resume so that it has the best possible chances of getting through.

In this guide:

• A machine learning resume sample better than most.
• How to create the perfect machine learning resume.
• How to write a resume for machine learning jobs that stands out.
• Expert tips and examples to boost your chances of landing a job in machine learning.

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Machine Learning Resume Example

Now here’s how to write a machine learning resume they’ll love:

1. Choose the Right Machine Learning Resume Format

 

People don’t want to deal with resume format outliers. Make sure your resume format is exactly what recruiters expect to see:

Machine Learning Resume Format

• Use the reverse-chronological resume formatand put your most recent successes first. If you work mostly as a freelancer, you might want to consider the functional (skills-based) resume format.
• For a neat resume layout, pick a proven resume font like a Noto, Garamond or Arial in 11–12 pt.
• Use one-inch resume marginsand lots of white space.
• Submit a one-page resume. Go to a two-page resume only if you have 15+ years’ experience.
• Outline your resume like this: Header, Summary, Experience, Education, and Skills.
• Perfect resumes are ATS-compatible. So choose a modern resume template, but make sure it doesn’t have visual elements such as infographics. Visuals look cool, but they're not easily machine-readable, so reliable ATS resume templates have a good reason to avoid them.

Expert Hint: How to write a resume fast? Tailor it to the job description. Consult the job ad at every step of the process. Include only those things that are relevant to the job.

2. Start With a Compelling Resume Summary

Every resume should start with a resume profile. A profile can be a resume objective or summary.

You may have written resume objectives for entry-level jobs, but there are no entry-level machine learning jobs.

Even if you’re applying for your first ML job or an ML internship you have a lot of relevant experience—in AI, software engineering, data science, and so on. So start your machine learning resume with a resume summary.

Use:

1. One adjective (efficient, inventive, industrious)
2. Job title (Machine Learning Engineer)
3. Years of experience (3+, 7+)
4. How you intend to help (push OpenCV-based development to next stage)
5. Your most impressive 2–3 achievements (developed and shipped 11 OpenCV machine learning solutions, helped to generate seven patents)

These machine learning resume summary examples show how:

Machine Learning Resume Example—Summary

Creative machine learning engineer with 6+ years’ experience working in consumer data-mining and computer vision. Seeking to bring technical expertise and business-minded approach to bear on Shop-U-Track’s current projects. At Hi-Viz Systems, developed and shipped 11 OpenCV machine learning solutions and helped to generate seven patents.

Logically minded machine learning engineer with 6 years’ experience. Seeking to expand on ML and AI expertise with Shop-U-Track. At Hi-Viz Systems, developed and shipped OpenCV machine learning solutions and helped to generate patents.

The first example is data-driven. It sticks to concrete facts, and backs them up with numbers. It’s focused on what the candidate can do for the company, not the other way around.

Expert Hint: Wanting to start writing your resume from the beginning is totally understandable, but it’s better to write your qualifications summary last. You’ll be able to do a much better job this way.

3. Create the Perfect Machine Learning Job Descriptions and Skills Section

Your machine learning job descriptions have one job. To get you invited to a job interview.

Achieve this by describing what you were able to do for previous employers. Make your resume work history section a showcase of your achievements. Here's how to write a job description for machine learning jobs:

1. Go back over the job ad.
2. Note any requisite machine learning skills and duties.
3. Think of times you’ve used those skills to bring value to employers.
4. Write resume bullet points that describe and quantify those times.

These machine learning resume examples show how:

Machine Learning Resume Job Description

Machine Learning Engineer

Hi-Viz Systems

2017–present

• Designed OpenCV machine learning algorithm that evaluated to 82% efficiency.
• Developed and shipped 11 OpenCV machine learning solutions for automatic predictions and decisions.
• Improved and maintained common tools and infrastructure, freeing up over 10 labor hours per week in the long run.
• Helped to generate seven patents as part of a team of four machine learning engineers.

Same candidate, same situations, similar descriptions, very different effects. The first one leverages quantified resume achievements for maximum impact. Both do a good job of starting each bullet point with a resume power word, though.

Expert Hint: Got employment gaps on your resume? It’s not unusual, so don’t try to hide them. If you feel they need some explanation, do it in your cover letter.

That’s all for your work experience, now it’s time to add a resume skills section. The trick here is to be selective.

Filter your machine learning skills through the job ad. This list of skills to put on a resume is just a seed:

Machine Learning Professional Skills for a Resume

• Clustering algorithms
• Decision trees
• Ensemble methods
• Independent Component Analysis
• Logistic Regression
• Naïve Bays Classifications
• Ordinary Least Squares Regression
• Principal Component Analysis
• Singular Value Decomposition
• Support Vector Machines

• Communication
• Critical thinking
• Decision making
• Flexibility
• Interpersonal skills
• Leadership
• Organization
• Problem solving
• Teamwork
• Time management

Make sure to add both soft and technical skills to your resume. Aim at a list of 5-10 skills.

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4. Leverage Your Education to the Max

No machine learning resume is complete without an education section. Recruiters are interested, first and foremost, in what you can do, and your work history and academic background give them the best insight into this.

Keep your education section clear and concise. Include degree names (with majors), school names, and years attended. Add bullet points with thesis topics (for research Masters and PhDs), achievements, and any other facts that point to your machine learning skills.

This machine learning resume sample shows how:

Machine Learning Resume Example—Education

MEng in Artificial Intelligence, University of Cincinnati

2013–2015

• Pursued a passion for business studies.
• Excelled in applied mathematics and statistics coursework.

BS in Artificial Intelligence, Carnegie Mellon University

2009–2013

Applying for an ML internship or your first ML job? Add more bullet points detailing projects, relevant coursework, and accomplishments that show how you’re on a collision course with a successful career in machine learning.

5. Stack Your Machine Learning Resume With Added Sections

It’s taken you quite a while to gain the expertise you need to work in machine learning. There’s a lot that won’t fit into the categories of work experience, education, and skills. Add one or two extra resume sections to flesh out the picture:

• Additional Activities
• Foreign Languages
• Courses Completed
• Awards
• Hobbies and Personal Interests
• Volunteering on a Resume
• Certifications
• Professional References
• Machine learning projects

These two ML resume examples show how there’s a right way and a wrong way to do this:

Machine Learning Engineer Resume Sample—Additional Sections

Professional Memberships

• Association for the Advancement of Artificial Intelligence (AAAI)
• Data Science Association

Programming Languages

• Python
• Java
• C
• C++
• JavaScript
• R
• Scala
• Julia

Computer Skills

• LibreOffice
• Microsoft Office
• Firefox
• Thunderbird
• Touch-typing

Hobbies

• Flying drones
• Recovering data off erased HDDs
• Bird watching

The second gets a couple of important things wrong: It’s not really relevant to the job at hand. Hobbies and interests can be a great addition, but they have to be directly and demonstrably relevant. And including the most basic of computer skills in your resume doesn’t make much sense when you’re able to pick up any new programming language within a day (or two for Haskell).

One last thing. Learn how to write a cover letter to seng along with your machine learning resume, unless you’ve been explicitly asked not to. If you don’t, you run the very real risk of having your machine learning resume rejected at the outset.

And if you’re emailing your job application, your cover letter doesn’t have to be even one page long.

Double your impact with a matching resume and cover letter combo. Use our cover letter generator and make your application documents pop out.

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Key Points

For a machine learning engineer resume that gets interviews:

• Use the machine learning resume template given at the beginning. You won’t find a cleaner approach.
• Put machine learning resume achievementsin your summary, work history, and education sections to let the facts do the talking for you.
• Select for the right machine learning skills. The job ad and your experience are the only data sets you’ll need here.
• Write a machine learning cover letter. Showcase your achievements as you demonstrate your communication skills.

Need more data points on how to write a winning machine learning resume? Leave any questions, comments, and feedback down below and we’ll be happy to get back to you.

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