Machine Learning Resume Examples and Writing Guide

Landing a machine learning job requires technical skills and expertise, and you’ll need to showcase this in a professional resume to help you get your dream position. Here are some aspects you should highlight for the recruiter in a machine learning resume:

• Your professional certifications showing your expertise
• Familiarity with data science principles
• Knowledge of various programming languages
• Your machine learning work experience

Header

 

Feature your contact information in your header. Include your full name, email address, address, phone number, and relevant social media like your LinkedIn profile or other professional portfolios. You should include this information in the header so that it is easy for the hiring manager to contact you if necessary.  

 

 

Your resume summary or objective is a brief paragraph that goes at the top of your resume. 

 

A resume summary is a better choice for those with plenty of experience since it is a snapshot of your career highlights thus far. It summarizes your strengths as a candidate in two or three sentences:   

 

Dedicated machine learning engineer with over five years of experience in designing and developing machine learning algorithms. Experienced in implementing analytics for different kinds of datasets. Versatile team player with a proven track record of finding innovative solutions.   

 

The resume objective, on the other hand, is a better option for those without much experience since it is aspirational. You use it to define your career goals and objectives. 

 

 

Your skills section needs to show you have the broad technical skill set required to be a competent machine learning engineer. Consider listing the following technical hard skills:

• Data structures
• Data modeling/data mining/data analysis
• Data visualization
• Predictive modeling
• Statistical modeling
• Regression
• Clustering and classification
• Web scraping
• Knowledge of Python/Java
• Knowledge of natural language processing (NLP) principles

However, don’t keep the focus solely on machine learning skills. Companies always want to see that you have the intangible abilities (also known as soft skills) to excel in the role, too. All companies value transferable skills like teamwork, communication skills, problem-solving and project management.

 

 

In your work history section, you’ll list recent relevant roles in reverse chronological order, along with a few major responsibilities and accomplishments for each role. Include any work on machine learning projects or computer science-related positions to establish your credibility for the recruiter.   

 

Try to list only professional experience that is relevant to the advertised role. Search the job description for guidance on particular duties and achievements that match up with your previous roles.

 

 

In your education section, further establish your credibility by listing any major academic qualifications you may have.  There aren’t many courses available that are entirely focused on machine learning because it’s a relatively young field. As a result, an undergraduate bachelor’s degree in a related discipline, such as computer science, statistics, electrical engineering, mathematics or the physical sciences, is frequently accepted, along with any more specialized coursework.

 

 

Having awards in machine learning is a great asset to add to your resume and will really make you stand out against other candidates. Whether these achievements are regarding AI or a specific industry experience, it is good to include them in your job application! 

 

 

If you don’t have relevant education in machine learning, there are multiple certifications that you can note of instead. For example, completion of online courses in areas such as software development and programming skills can bolster your resume. 

There are a multitude of resume examples and templates available for you to use that can fit into your machine learning role. Simply follow our example above to ensure you have filled in all the relevant information that machine learning recruiters will be looking for! 

Now that we’ve gone through the structure of a machine learning resume, here are some extra writing tips that will help you when crafting your own resume.

 

Use industry-specific jargon and acronyms to showcase your expertise. References to the knowledge of  SQL, Spark, Hadoop, TensorFlow and NumPy may not mean anything to most people, but they will indicate to the recruiter that you know your stuff. In addition, you can use the job description to customize your resume to the advertised role, hitting specific keywords that the recruiter is looking for.

 

Last, don’t write a machine learning resume without help! Use our resume builder for job-specific writing tips on how to create the perfect resume with resume templates.