I had an interview yesterday and the first thing they said on the phone was: “Wow! I love your resume.” Patrick
I love the variety of templates. Good job guys, keep up the good work! Dylan
My previous resume was really weak and I used to spend hours adjusting it in Word. Now, I can introduce any changes within minutes. Absolutely wonderful! George
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:
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.
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.
How to write a job description for machine learning jobs:
Go back over the job ad.
Note any requisite machine learning skills and duties.
Think of times you’ve used those skills to bring value to employers.
Write resume bullet points that describe and quantify those times.
These machine learning resume examples show how:
Machine Learning Resume Job Description
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 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.
Nail it all with a splash of color, choose a clean font, and highlight your skills in just a few clicks. You're the perfect candidate, and we'll prove it. Use our resume 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.
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
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
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—
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.
Want to try a different look? There's 21 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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