Machine Learning Resume Examples [Also for an Engineer]

You’re a diviner of data, an expert trainer of ML dragons. Make sure your machine learning resume does your skills justice. Read on to find out how.

Bart Turczynski
Editor-in-Chief
Machine Learning Resume Examples [Also for an Engineer]

Abstract: Machine learning is at the heart of common artificial intelligence applications like email filtering and computer vision. The purpose of your machine learning resume is to show you’ve got the theoretical knowledge and programming skills to push ML boundaries as well as the soft skills to be a productive member of a team.

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 ML resumes—

 

Filtering and eliminating and then comparing and assessing—

 

Until they find that one candidate that ticks all the boxes better than anyone else.

 

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 ML job descriptions for your 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 templates

 

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Looking to share your knowledge or launch a technical writing side hustle? See our guides:

 

 

Machine Learning Resume Example

 

Thomas Howard

Machine Learning Engineer

 

Personal Info

 

Phone: 419-763-3201

E-mail: thomas.h.howard@reslab.com

linkedin.com/in/thomashhoward

 

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.

 

Experience 

 

Machine Learning Engineer

Hi-Viz Systems

March 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.

 

Machine Learning Intern

SnoopCorp

May 2015–February 2017

  • Used Juniper router data to develop machine learning models that identify anomalies with 94% accuracy and 0.1% false positives.
  • Built predictive models with decision trees to track users preemptively, up to three URLs ahead.
  • Identified and built 11 new datasets to enhance models and decision making.
  • Developed, validated, and implemented newly created models into three proofs of concept.

 

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

 

Professional Memberships

 

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

 

Programming Languages

 

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

 

Key Skills 

 

  • Clustering algorithms
  • Decision trees
  • Ensemble methods
  • Independent Component Analysis
  • Logistic Regression
  • Communication
  • Critical thinking
  • Problem solving
  • Teamwork
  • Project management

 

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

 

1. Choose the Right Machine Learning Resume Format

 

Don’t be like that intern—

 

Feeding in randomly formatted data sets and wondering why they’re not being parsed.

 

It’s not even a matter of satisfying Applicant Tracking Systems (ATSs)

 

People won’t want to deal with resume format outliers.

 

Make sure your resume format is exactly what recruiters expect to see:

 

Machine Learning Resume Format

 

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

Good Example
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.
Bad Example
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.

Which would you hire?

 

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.

 

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

Good Example

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.
Bad Example

Machine Learning Engineer

Hi-Viz Systems

2017–present

  • Designed efficient OpenCV machine learning algorithm.
  • Developed and shipped OpenCV machine learning solutions for automatic predictions and decisions.
  • Improved and maintained common tools and infrastructure.
  • Helped to generate patents as part of a small team of 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:

 

Be selective.

 

Filter your machine learning skills through the job ad—

 

The skills list below 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.

 

The ResumeLab builder is more than looks. Get specific content to boost your chances of getting the job. Add job descriptions, bullet points, and skills. Easy. Improve your resume in our resume builder now.

 

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Nail it all with a splash of color, choose a clean font, highlight your skills in just a few clicks. You’re the perfect candidate and we’ll prove it. Use the ResumeLab builder now.

 

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

Good Example

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:

 

 

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

Good Example

Professional Memberships

 

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

 

Programming Languages

 

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

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 if statement—

 

Always include a cover letter 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 builder and make your application documents pop out.

 

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Want to try a different look? There’s 18 more. A single click will give your document a total makeover. Pick a cover letter template here.

 

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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Bart Turczynski
Bart Turczynski is a career expert and the Editor-in-chief at ResumeLab. His career advice and commentary has been published by Glassdoor, The Chicago Tribune, Workopolis, The Financial Times, Hewlett-Packard, and CareerBuilder, among others. Bart’s mission is to promote the best, data-informed and up-to-date career advice on ResumeLab’s blog as well as through numerous online communities and publications. At ResumeLab, Bart manages a large team of career experts and editors in delivering top-quality, unique content. Bart’s life-long passion for politics and strong background in psychology makes all the advice published on ResumeLab unique, accurate, and supported by detailed research.

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