People with machine learning skills are in high demand. According to Forbes, the global market for Machine Learning Engineer jobs is projected to grow at a compound annual growth rate of 42.8%. And that’s no surprise because machine learning is now used in nearly every industry — from healthcare to agriculture to energy.

If you’re excited about artificial intelligence, algorithms, coding, data, and automation, a career in machine learning could be the right fit for you. It could also give you an average salary of $114,579, a figure that’s expected to increase by 13% by 2026.

So it should come as no surprise that there can be a lot of competition if you’re trying to land a job as a Machine Learning Engineer. The good news is that, while there’s no singular path to getting hired, there are a few tried and true ways to increase your chances of landing your dream job in this exciting field.

First, narrow down the industry you want to work in

As a Machine Learning Engineer, you can take your pick as far as which industry to work in — machine learning is used in finance, manufacturing, transportation, healthcare, food and beverage, advertising, energy, and automotive just to name a few. So we suggest focusing your job search on one or two sectors that you’re really interested in.

For example, if you’re a career changer who worked as a bank teller, you might consider looking for a position with a finance company. Your background could bring a unique perspective to the company, and give you an advantage during the interview process.

While you’re narrowing down which industry you want to work in, you’ll also want to consider the size of the companies you’re looking at. Larger companies may have more opportunities for advancement, but you may have a narrow scope of responsibilities. At small-to-midsize companies, you may have more responsibility, which has its own pros and cons.

Learn, learn, learn

Machine Learning Engineers have a particular set of skills, no matter which industry you decide to work in. And the competition is high, so you really have to know your stuff to land a job.

In addition to knowing a handful of programming languages — Python being the most popular language for machine learning — you’ll want to focus your learning on basic computer science principles. You should have a strong grasp of algorithms and data structures, data visualization, statistical modeling, quantitative analysis, and cloud computing.

Other programming languages and some typical tools you’ll see listed on machine learning job descriptions include R, C++, Java, TensorFlow, Pytorch, Scikit-learn, NumPy, Pandas, Apache Spark, and OpenCV.

Each company will have its own requirements, but to prepare for a career in machine learning, you can brush up on or learn new skills you frequently see in job posts.

Get experience

Once you feel confident in the basics, you can look for ways other than a full-time job to gain experience. This might look like a personal project, freelance gig, or volunteer work.

Don’t worry if you can’t find a project or volunteer work that specifically involves machine learning. Can you find a company looking for a Python programmer for 10 hours a week? Great — that’s real-life coding experience that will get you one step closer to a full-time role.

Build a strong portfolio

Creating a portfolio that showcases all of your best work is one of the most productive things you can do to increase your chances of getting hired for any technical position. It’s how you’ll grab the attention of the hiring manager and prove you can do the job they’re looking to fill.

Your portfolio should include sample projects as well as a GitHub profile containing all the code you wrote over the past several months. If you’re looking for project ideas or ways to add work to your portfolio, a number of our Skill Paths have portfolio projects built into the curriculum, like Analyze Data with Python and Build Deep Learning Models with TensorFlow.

One bonus of building a robust portfolio is that you gain a lot of experience while working on all the projects you include in your portfolio. Also, your portfolio will include a lot of the same information that you’ll put on your resume, so spending some extra time on your portfolio will probably make building your resume a bit easier.

Prepare for the interview process

Being prepared for each step of the interview process is crucial. It’ll usually kick off with a phone screening where you should be prepared to answer why you’re interested in the position, as well as questions about your background and your familiarity with certain tools you’d use on the job. If this screening goes well, the next step is oftentimes a technical interview.

Technical interviews are more in depth, and you’ll be asked a variety of questions related to machine learning, as well as other technical and behavioral questions.

A few tips for the technical interview:

• You’ll most likely be given a challenging scenario during the interview and asked how you’d approach it. They may ask about how you would preprocess, augment, and acquire data. You may also be asked to execute the code on a computer or given a whiteboard or sheet of paper. So you might want to practice hand-writing code to be prepared for different scenarios.
• You should expect to be asked to solve a larger technical task. This might be something you’d do over a day or two and turn back in. Before turning in your code, write a short report that outlines the steps you took to solve the problem. Clarify which code you wrote and which code you copied and pasted, and be sure to add functionality to the code you pasted into your project.

Hiring managers expect you to use some existing code but also want you to demonstrate what else you can do. Don’t forget to include tests for the code you wrote.

• There’s always a chance that you won’t know the answer to a question. Prepare for how you’ll respond if you don’t know, and don’t let that influence the rest of your interview.

One way to respond to questions you don’t know the answer to is to explain how you would find the answer. Discuss what resources you might use and your general approach to dealing with knowledge gaps.

Getting a job as a Machine Learning Engineer is an involved process that requires a chunk of time, but it’s worth it! Not only is your earning potential high, but you also have the option to work in a lot of different industries on a variety of challenging and interesting problems.

Interested in going down this path? Check out some of Codecademy’s machine learning courses and brush up on your skills.  

Machine Learning Courses & Tutorials | Codecademy

Machine Learning is an increasingly hot field of data science dedicated to enabling computers to learn from data. From spam filtering in social networks to computer vision for self-driving cars, the potential applications of Machine Learning are vast.

Python Courses & Tutorials | Codecademy

Python is a general-purpose, versatile, and powerful programming language. It’s a great first language because it’s concise and easy to read. Whatever you want to do, Python can do it. From web development to machine learning to data science, Python is the language for you.

While being “between jobs” is nothing to be ashamed of, it can invite questions during the job-hunting process that you’ll want to be prepared to answer. But there’s no one-size-fits-all solution: How you approach an employment gap on your resume and during an interview can depend a lot on why you have one in the first place.

First things first: If you feel like you’re one of the only people dealing with an employment gap, that’s simply not true. In fact, the pandemic has left an estimated 114 million professionals across the globe out of work to some extent for pandemic-related reasons, including everything from business closures to unsafe working environments to caregiving responsibilities. The pandemic also sparked The Great Resignation, during which millions of workers have left their jobs for a range of reasons.

So you’re absolutely not alone in this. And with a little practice, you can confidently address an employment gap on your resume and during an interview. Here are some tips to get you started.

Employment gaps on resumes: dos and don’ts

Resumes are kind of like first impressions, so you want to take some extra time and think through the best way to show an employment gap on your resume.

Do: Use formatting to your advantage for short gaps

One way to lessen the impact of a short employment gap, say a 2- or 3-month gap, is to write your employment period in years versus the year and month.

Here’s an example: Say you worked at Priceline from February 2018 through October 2020, and then you weren’t employed from October through December 2020. Then, you got a job at Atlassian in January of 2021. Instead of including the month you were hired and the month you left Priceline, you could show your employment history like this:

2021 – Present

Software Engineer

Atlassian

2018 – 2020

Junior Software Engineer

Priceline

Don’t: Hide longer gaps

For a long employment gap that’s more challenging to explain, your first instinct might be to hide it. But that’s not a good idea. Employers want honesty from the start.

One way to address a longer gap on your resume is to add a short explanation next to the date. Keep it short — don’t feel obligated to give unnecessary personal details, but give enough information so the hiring manager knows that you’re not hiding anything. You could include a phrase like “took time off to care for an ill family member” or “laid off during a merger” by the dates on your resume.

Do: Make your cover letter count

If you put the reasoning “laid off during a merger” on your resume, then you might want to use your cover letter to explain more about that. Did your job become obsolete during the merger? Explain this. Were you the most recently hired employee with your job title and the company only had room for one of you? Let the hiring manager know this in your cover letter.

You want to be concise but you don’t need to spend a lot of time on this, and you certainly don’t want to write it in a way that makes it seem like you are resentful. Just state what happened in a matter-of-fact way. You’ll have a chance to talk it through during an interview if the hiring manager wants to hear more.

Do: Highlight the positives

Did you volunteer during your employment gap? Finish a cool personal project? What about freelance work? You could list something like this on your resume in the same way that you would another job. So you’d want to include your job title, company name, job description, accomplishments, and dates of engagement.

If you decided to switch careers and took time off for education, you could use the job title “Student” and list this where your employment gap shows up on your resume. List what courses you took and certificates or degrees you might have.

Employment gaps during an interview: dos and don’ts

More than likely, you’ll get at least one question about your employment gap during an interview, so you’ll want to be ready to explain how you spent your time. Keep these tips in mind when you’re answering questions related to a work break during an interview.

Do: Practice your response

It’s really helpful to practice how you’ll respond to questions about your employment gap. Literally say your response out loud. You can even go a step further and ask a friend or family member to play the role of the interviewer and give you a chance to respond to a real person.

Bonus: They might have some advice if you’re still working out the wording for your answer.

Don’t: Bad mouth your former manager/employer

Unfortunately, sometimes employment gaps happen because something went wrong at work. Maybe you left your job because you didn’t get along with your manager, and then the pandemic hit and no one was hiring. Or maybe you quit your job for one that was going to pay you more, but it didn’t work out and then you were left unemployed.

Either way, remember that you don’t need to go into a lot of detail regarding your employment gap, and you definitely should not bad mouth anyone from your previous company. A concise “it wasn’t the right fit for X reason” can often do the trick. Once you answer, try to take the conversation in a more positive direction, like the volunteer work you did while between jobs or what you learned from that experience.

Do: Show you’re excited about this particular job — not just any job

Most hiring managers will understand that employment gaps are par for the course during any given career journey. That said, there are some who might get the wrong impression about your ambitions or assume you are applying to lots of jobs indiscriminately. This means it’s on you to show that you really want this job, and there’s no question that you’re ready to get back to work.

You don’t have to say much to get ahead of this, though. You can stress that despite your best efforts, you have not found the right fit — but emphasize that you’re being selective about your next move to find the right long-term fit, not just the first job that comes along. This type of simple statement can show potential employers that you’re approaching this process thoughtfully.

Moral of the story? No matter the reason for your employment gap, you should explain it clearly and honestly on your resume and during an interview. And by incorporating a few simple tips, you’ll be prepared for whatever comes your way.

Interview Prep Courses & Tutorials | Codecademy

Interviewing is an important step in your journey towards landing a job in tech. Technical interviews let you showcase your skills and knowledge, but practice is key. You’ll need to understand technical concepts and be prepared to talk through solutions with your interviewers.