To get in, you need a Ph.D. level formal education or expert-level working experience together with a solid machine learning engineer resume.
But don’t give up yet!
Even if you don’t have all that formal education and industry experience, you can still get interviews and get hired if you write your resume demonstrating how your previous experience is going to be relevant to this new job.
Let’s break this down step-by-step!
This article includes:
- Example machine learning engineer resumes you can copy.
- Resume format, layout, and templates your hiring manager will enjoy reading.
- A step-by-step guide to writing each section of your resume.
- Pro tips to make your resume stand out from the rest.
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Machine Learning Resume Sample
If you need further inspiration for writing your machine learning engineer resume, we have also listed other engineering fields for your reference👇.
How much does an average machine learning engineer make?
According to payscale.com, the average salary of a machine learning engineer is $112,000/ year 💰. It could go anywhere from $80k to $160k, depending on your experience.
A great resume will help you land a job with a higher salary than the industry average. Imagine spending 10 minutes reading this article and generating an additional $1000 each month.
How to Write a Resume to Get Top-of-the-Class Machine Learning Jobs?
If you want a machine learning engineer job at Apple, Intel, or Microsoft, you should know what happens to your resume after you click “SEND”.
Your application goes through a series of shortlisting before they call you for an interview. First, it will go through an applicant tracking system (ATS) which will do the initial shortlisting based on your resume keywords.
HR will only find the shortlisted applications through the system. Manually selected applications by HR will be sent to the relevant departments, and they’ll pick who they want to talk to.
To get an interview, your resume should be strong with the following:
- Relevant keywords
- Standard resume writing practices
- Relevant Skills and results
So let’s get your resume standards right, picking up the perfect layout and format to write the resume.
Machine learning engineer resume layout
Your resume needs a plan like any project you start – this is called the layout or structure of your resume.
In this, you define the headings, subheadings, and information you put in your resume.
When you start with a clear layout, you know exactly how long your resume will be and how to optimize it to effectively use the space. In addition, you won’t miss any important information that should go in the resume.
We recommend the following layout for a machine learning engineer resume:
- Header: name and contact information
- Professional summary statement
- Work history
- Additional sections (certificates, interests, and publications)
Machine learning engineer resume format
Your resume format defines the order in which you present your experience.
There’re 3 standard resume formats in use:
- The functional (skill-based) format: Your experience section is written based on the relevant skills you developed and demonstrated during your work. This format is most suitable for entry-level candidates.
- Reverse chronological order (traditional) format: In this, your most recent experience will be given priority, and the rest will follow the reverse chronological order. This is widely used and suitable for experienced candidates.
- Combination format: Both the abovementioned formats will be used in this format.
We suggest you use a reverse chronological format to list your experience as much as possible. The reason is that most hiring managers are familiar with this format making their resume reading process more smooth.
In fact, your most recent experience gets the hiring managers’ attention.
Why is keyword research important for machine learning engineers?
Including the right keywords at the right keyword density would be important to pass the ATS test.
You can do the keyword research for your resume using the following sources:
- The job advertisement/ job description
- Company’s website
- Industry Blogs and forums
- Our comprehensive guide to Keywords for your resume
Make sure you include keywords on your resume in a natural and relevant way. Keyword overstuffing would harm your resume ranking. Also, avoid tricks that could flag your resume, such as hiding white text on the resume to get through the ATS.
Start Your Machine Learning Engineer Resume with the Header
Start your machine learning resume with a header. The header should consist of your name and contact information. This is a short yet important section on your resume. The accuracy of the information here is vital for the hiring manager to get back to you.
A good & a bad header
Here’re some of the things you should keep in mind while writing this section👇
- Start your header with the name.
- Highlight the job position you’re applying for.
- Write your mobile number and email.
- Do not write the full mailing address in the header.
- Put the link to your LinkedIn account or portfolio. Make sure they are up to date.
Machine Learning Resume Summary to Hook the Hiring Manager
Include an excellent resume summary at the beginning of your resume to encourage the hiring manager to read your full resume.
These 3 to 4 lines at the top of your resume will decide the rest of the reading experience. So make sure it’s well-written.
Writing top professional summaries is not as technical as machine learning. But if that’s the language you prefer, consider writing it according to the following formula.
Sentence 01: (an adjective to describe you) machine learning engineer with (years of experience) in (key skills and expertise) seeks to join (company) to (why).
Sentence 02: In my previous job at (company), (your key achievements).
As you have to write professional summaries tailored to every job you’re applying for, the above formula would help you save a lot of time.
Here’s to get inspiration to write yours:
A professional objective/ objective summary and a professional summary are pretty much the same. The professional summary is used for experienced candidates, and the objective summary is used for entry-level candidates or freshers to highlight their passion and career objectives.
Still, you should demonstrate your achievements and key skills to make the hiring manager’s eyeballs roll.
Demonstrate Your Machine Learning Experience
This is the section that decides whether your salary stays at the average or above it. Before that, this section will determine if you will get an interview or not.
Hiring managers are willing to overlook every other mistake on your resume if you have a strong experience section.
Here, most machine learning engineers copy and paste the roles & responsibilities from their previous job descriptions. Hiring managers are the people who create these, and they don’t wish to see them in your resume. They really care about your achievements and accomplishments in your role to understand whether you’ll fit the machine learning position.
Check out the following examples and take note of our Pro Writing Tips.
Experience section for a machine learning engineerIt is important for a senior machine learning engineer to demonstrate both their technical expertise and soft skills such as leadership and communication skills.
In addition, follow these guidelines to write an impressive experience section:
Experience section for an entry-level machine learning engineer
It’s always tough when you need the experience to start your first job when it’s very much clear that you first need a job to get experience.
Here’s the truth. The recruiter wants someone with experience.
What if you don’t have experience?
Then you don’t have to show it.
Even if you’re applying for your first job, you should fill your experience section with your internships, personal projects, academic projects, and other relevant experience.
Never keep the experience section empty!
Show your enthusiasm and confidence throughout your writing.
Will Your Education Make a Difference?
For machine learning engineer jobs, recruiters will highlight a specific set of academic qualifications or formal education qualifications as prerequisites.
A bachelor’s degree in computer science or a related field would be required in most cases. However, most applicants possess Master’s degrees and Ph.D. level academic qualifications for machine learning engineer position.
In writing your resume, the number one principle is to play with your strengths. Highlight your strengths and hide your weaknesses.
If you have a solid academic profile, use some quality space to showcase it. If not, state your degree and move on to writing your experience and projects sections.
It is best to write your education section just after your experience section. To list your degrees:
- Use a consistent format.
- Include the key learning outcomes from each course – the GPA – the year of graduation – and the university’s name.
- Do not forget to mention any special academic achievements you have made.
Machine Learning Resume Skills
Your skills section should include a mix of soft skills and hard skills.
Soft skills are a candidate’s personality traits, while hard skills are technical skills required to carry out the job.
State the key technical skills you think will be important at the targeted position.
Decide on the soft skills based on the seniority of the position you’re applying for.
For managerial positions, skills such as leadership, communication, negotiation, and business intelligence would be important, while for technical positions, skills such as teamwork, attention to detail, and time management would be relevant.
Always refer to the job description, as most ads contain information about the ideal candidate the hiring team is looking for.
Here’re some example machine learning skills for the machine learning engineer profile:
Soft skills for machine learning engineers
- Analytical skills
- Attention to details
- Clear communication
- Time management
- Organizational skills
- Interpersonal skills
Hard skills for machine learning engineers
- Project management
- Data analysis: Tableau, Microsoft office suite
- Natural Language Processing
- Web Scraping
- Data clustering & classification
Make a Pleasant Surprise with Additional Sections
Though your machine learning engineer resume is ready, it needs a couple of additional sections to make it an impressive one for the hiring manager.
Additional sections provide a pleasant surprise with important information about the candidate – some of these could make your application stand out from the rest.
Here’re some of the additional sections you may consider:
- Computer skills & certifications
- Professional associations
- Awards & Honors
Computing skills & certifications
Do your research on what skill certificates will be valuable for the machine learning job. Some skill certifications are free, and some are paid – whichever it is, you’ll be investing a lot of time. Therefore, make sure you pick the right certifications to follow.
Here’re some of the related certifications for machine learning engineers:
- AWS Certified Machine Learning
- Professional Machine Learning Engineer by Google
- Azure AI Engineer Associate by Microsoft
- IBM Machine Learning Professional Certificate
In addition, there’re MBA and MSc programs conducted by many technology universities for machine learning engineering.
Machine learning projects
If some of your previous projects give you more exposure to machine learning work than your job, you should emphasize them in an additional section.
Use a clear format to write the project work. Mention the project name, objective, duration, budget, accomplishments, and challenges faced, if any.
If there’re publications or patents in your Master’s degree or Ph.D., you can mention them in a separate section to draw the hiring manager’s attention. This will demonstrate your research skills and academic fluency.
Writing this section highly depends on the organization you’re applying for. Some don’t care about your interest in reading books and running marathons.
If your interests align with the company’s mission or if you want to communicate a different side of yourself aside from working with data, you could write this section.
Tips to Improve Your Machine Learning Resume
- Proofread your resume – use Grammarly to do basic corrections.
- Invest in skills certifications – the time and money you invest in acquiring those certifications will give you the best return.
- Continuously optimize your resume experience section based on the feedback you get.
- Consider creating your resume with a modern resume template that matches your profile.
Complement Your Resume with a Cover Letter
The resume is the main component of your job application. However, there’s another essential part of it: the cover letter.
A cover letter is a tailored document you write directly to the employer or the hiring manager highlighting your interest in the position, relevant machine learning engineer skills, and experience.
A machine learning engineer resume should have a cover letter, as most machine learning candidates come from different fields. The cover letter is where the candidate gets to explain how their previous experience will fit the new context.
If the position interests you, put away the laziness and write a professional cover letter along with your resume. Don’t just click the “EASY APPLY” on LinkedIn.
If writing cover letters consume a lot of time, you haven’t tried our cover letter builder. Check out how to create a cover letter with the same template you used to create your resume within 10 minutes.
What industries offer jobs for machine learning engineers?
Machine learning engineers are in high demand in industries where many data-driven decisions are made.
Following are some of the industries they’re hired in:
Which companies pay the highest salaries for machine learning engineers?
Salaries for machine learning engineers would depend on their experience level and the impact of their work on the organization’s bottom line. Here are some companies with the best salaries and benefits for machine learning engineers:
- The Boeing Company
- Lockheed Martin Corporation
- Apple Computers
- Ford Motor Company