Are you looking to kick off a career as a machine learning professional? If so, it’s a great time to rewrite your resume, update your LinkedIn profile, and get ready to catch the attention of potential employers. In order to design the perfect machine learning engineer resume, you must be clear on what positions you’d like to apply for and make certain that your resume communicates that you have the skills and experience to flourish in that role.
So how do you design the perfect resume for a machine learning professional? This article will walk you through everything from resume layout to how present your technical skills and relevant experiences so that you stand out among the applicants.
Resumes: What Are They?
First off, what is a resume? A resume, or a curriculum vitae (CV), is a brief professional document that outlines an individual’s education, work experience, skills, achievements, and additional information that presents their qualifications to a potential employer. Resumes are used in the job application process in order to offer prospective employers a concise snapshot of their background and suitability for a specific job position.
Resumes are typically composed of the following five sections:
Contact details: including your complete name, phone number, email address, and potentially a link to your LinkedIn profile.
Introduction: a concise summary of who you are; it shouldn’t be more than 2-3 sentences.
Education: includes your educational background, degrees, majors/minors, and educational awards if relevant.
Experience: includes relevant work experience, listing the name of the company, summary of your work, the location, and the time period in which you worked there.
Skills: both hard and soft skills should be listed, make sure that the skills you choose to highlight are relevant to the position you’re applying for.
Why are resumes important?
In the days of LinkedIn, professional websites, and extensive job applications, why are resumes still relevant? Despite ongoing developments in employee recruitment processes, resumes remain integral in the modern job search process. Here’s why:
A resume is often the first contact you’ll have with an employer, meaning they’re crucial in catching their eye and leaving a great first impression.
Additionally, these professional documents are standardized, customizable, and great for showcasing your relevant qualifications and skills.
Today, many companies have integrated Applicant Tracking Systems (ATS) to scan resumes and determine whether or not candidates pass the initial screening process.
Knowing this, it’s crucial to create an easy-to-read resume, keep it up-to-date, and include important keywords and phrases that AI or machine learning technologies will identify such that your resume helps you stand out in the employee selection process.
Resumes for Machine Learning Professionals
If you’ve made it this far it’s surely because you’re on a mission to craft the perfect resume to land that dream machine learning job. We know that there’s been an increase in the field of machine learning, with AI and machine learning jobs increasing by almost 75% over the last four years, but don’t let this mislead you. Even though the tech industry is growing, not every machine learning job is a position you may be interested in. A solid resume may make all the difference between:
A humble salary and a salary that transforms your life
A position that grants greater flexibility or remote work opportunities as opposed to an in-office role
An organization whose values and business approach is one you stand by and can see a future being part of as opposed to one you may not align with
Crafting that resume should not be taken lightly because it may be the ticket to securing a role that truly aligns with your values and personal and professional aspirations.
Types of resumes in machine learning
It’s upon you to determine how you’d like to structure your resume. That said, there are three standard resume layouts in machine learning. They include:
Reverse-chronological resume: lists your work experience in reverse chronological order, beginning with your most recent job and walks a potential employer through your previous work experiences. This style of resume is great for machine learning professionals who have strong work experience in relevant roles. It’s an ideal way to showcase your career progression and highlight your achievements throughout your professional trajectory.
Functional resume: centers your relevant skills and qualifications as opposed to your chronological work history. It’s an ideal resume for someone who may have many gaps in their work history, or for folks who’ve changed career tracks and may not have as much relevant work experience to highlight. If you’re new in the field of machine learning, choosing a functional resume that highlights your skills, technical experience, and achievements without emphasizing your employment timeline will help you make a stronger first impression on potential employers.
Hybrid resume: combines the reverse-chronological resume and the functional resume. It combines elements of both and is great for professionals who want to emphasize specific skills or pivotal moments in their career, as opposed to laying out their entire career history. The hybrid resume is more and more common as it allows job applicants to customize their resume depending on the role they’re looking to secure. It may be the perfect resume format for you if you want to highlight very specific aspects of your profile and work history.
These are the three most common resume types for machine learning professionals, but undoubtedly these documents can take different formats if you’re interested in highlighting additional skills or specific professional accomplishments. Get clear on how you’d like to present yourself and select the resume format that best showcases you!
Different sections of your machine learning professional resume
Now that you’ve determined your resume structure and have selected a clean and professional layout, it’s time to showcase your skills and experiences and create the best machine learning resume. Whether you’re creating an entry level machine learning engineer resume, or a more extensive data scientist machine learning resume, you’ll want to make sure you build a machine learning resume that best represents you. Your resume should include the following sections:
Include a concise 2-3 sentences that summarize your expertise and career goals in machine learning. This professional summary can mention your years of experience, key skills, and any specializations or certificates that will help you stand out.
Tip: including your accomplishments is huge, but your resume would stand out even more if you could include actual data to back up your achievements.
Your resume should describe your work experience. Focus on your achievements and impact whenever possible. This is a great space to highlight projects related to machine learning, data analysis, and artificial intelligence.
Tip: emphasize any real world applications of machine learning that you’ve partaken in. This may include specific ways in which you streamlined business processes or developed innovative solutions utilizing machine learning or AI. For example, “improved model accuracy by 20%” or “led a team that completed X number of projects.”
Potential employers are going to quickly scan the section of technical skills in your resume. Include all programming languages that you’re familiar with (Python, R, Java, etc), machine learning libraries and frameworks (TensorFlow, PyTorch, scikit-learn), and any other relevant tools or applications.
Tip: in this section you may also list relevant certifications related to machine learning or data science, such as Coursera, edX, or additional industry specific certifications.
Soft skills are becoming more and more important in the field of tech. Include your relevant interpersonal skills like problem-solving, effective communication, teamwork, and adaptability. Today these skills are crucial in almost all tech work environments and play a huge role in determining if a candidate is capable of holding a specific role.
Including a projects section in your resume allows you to showcase personal work or side projects related to machine learning. In constructing the best machine learning resume, we’d recommend including the following in a section regarding machine learning projects for your resume:
Highlight personal work or side projects that relate to data science and machine learning. Begin by describing the problem, your role, and the tools, programs, or technologies utilized in addressing the problem. Finally, include the outcome of the situation and use data to show its importance.
If possible, include links to online demos of your projects so that employers can get a greater sense of your work.
Additional resume tips
Optimize for ATS: more and more companies use Applicant Tracking Systems (ATS) to quickly scan resumes for keywords in order to optimize their employee recruitment and selection processes. You do not want to have your resume get cut before an employer gets a chance to see it; be sure to include keywords for machine learning resumes.
Proofread and review: grammatical errors and typos are not only embarrassing, but do leave a negative first impression. Make sure that your resume is polished. Have a friend, coworker, or mentor proofread your resume in order to get feedback on its clarity and effectiveness.
Maintain a consistent design theme: once you’ve selected a design layout and theme, make sure you stick to it. Use the same fonts, colors, and layout such that your resume gives a professional and cohesive impression.
And that about covers it! Following these tips and tricks will help you design the perfect resume to land that dream machine learning role. If you are interested in kick starting a career in data science and machine learning, or you’d simply like to brush up on your skills, then you’re in the right place. Ironhack offers data science bootcamps that will prepare you to land that dream job.