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Machine Learning Engineer

Also goes by: AI Data Analyst, AI Engineer, AI Research Scientist, Data Scientist, ML engineer,

How much will I make?

Salaries can range by location and years of experience, but these are averages for the US.

according to Salary.com

Will I get a job?

Projected job growth is 82% for the period 2020-2030 in the US, according to the U.S. Bureau of Labor Statistics.

Total Openings
according to comptia.org

Who will I work for?

  • Tech Companies
  • AI Startups
  • Financial Institutions
  • Healthcare Companies
  • Automotive Companies

Machine Learning Engineer’s Daily Activities

No Machine Learning Engineer works alone! Machine Learning Engineers spend their days collaborating with designers, other developers, and product or project managers to bring machine learning programs to life. Below you will get a sense for what a day-in-the-life of a Machine Learning Engineer could be:

Collaborate With Your Team Members to Build machine learning programs

Machine Learning Engineers work hand-in-hand with their team members to create machine learning programs. In order to do this, you’ll need to have an understanding of a wide variety of skills including Python, R, Algorithms. Collaboration can take many forms, including planning and strategy meetings, design brainstorms, reviews, and pairing.

Code Your machine learning program

Much of a Machine Learning Engineer’s day is spent coding. In practice this means having a development environment set up on one’s computer that allows you to track your progress as you go.

Test Your machine learning program

One of the joys of working as a Machine Learning Engineer is that machine learning programs are ALWAYS breaking! As a Machine Learning Engineer one of your core duties is testing your machine learning programs for bugs and errors and working to fix them

How To Become a

Machine Learning Engineer

It’s absolutely possible to become a Machine Learning Engineer even if you have no prior experience in tech and no degree. In fact, a career as a Machine Learning Engineer is one of the best entry level jobs in tech. Read on to learn how to do it!


Learn The Required Skills

First things first, in order to become a Machine Learning Engineer you have to learn the required tech skills!


Python is a general-purpose coding language—which means it can be used for other types of programming and software development besides web development.

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R is a programming language used for statistical computing and graphics, widely used among statisticians, data scientists, and researchers for data analysis and visualization.


Algorithms are step-by-step procedures or sets of rules designed to solve specific problems or perform tasks in computing and other fields, helping computers process and analyze data efficiently.

Deep learning

Deep learning is a type of machine learning that uses artificial neural networks to learn from data.

Data Structures

Data structures are data organizations that allow for efficient access and manipulation of data.

Machine Learning

Machine learning is the process of developing machines, software programs, and other computer systems capable of “learning” and applying learned knowledge without specific instructions.

Statistical analysis

The process of collecting, organizing, summarizing, and interpreting data to draw conclusions, make inferences, and support decision-making.


SQL stands for “Structured Query Language” and it is a programming language used to manage data in relational database management systems, creating data structures, and accessing data in web development.

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Distributed computing

Distributed computing is the practice of running multiple tasks on multiple computers in a network. Distributed computing is used to solve problems that are too large or complex to be solved by a single computer.

Cloud Platforms

Cloud platforms refer to online services that provide scalable computing resources, storage, and services over the internet, enabling organizations to deploy, manage, and run applications without the need for on-premises infrastructure. The most commonly used cloud platforms are Amazon Web Services (AWS), Google Cloud, and Microsoft Azure.

Statistical analysis

The process of collecting, organizing, summarizing, and interpreting data to draw conclusions, make inferences, and support decision-making.

Big Data

Big data is a term used to describe data sets that are too large or complex to be processed using traditional data processing methods. Big data is often used to analyze customer behavior, predict trends, and make better decisions.

Code Efficiency

Code efficiency is the ability to write code that is both fast and reliable. Code efficiency is important for a number of reasons, including performance, cost, and scalability.

Version Control

Version control is the management of changes to documents, source code, or other files, allowing multiple users to collaborate and track revisions, facilitating teamwork and preventing conflicts.

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Build A Portfolio

The best way to demonstrate that you have the necessary skills—especially when you have no prior experience—is with a portfolio of professional quality coding samples.

Check out these blog posts for more:


Apply For Tech Jobs

Once you’ve learned all the required technical skills and built a killer portfolio, it’s time to dust off that old resume and LinkedIn profile and hit the pavement, or Internet superhighway as it were, in search of your first job as a Front End Developer!

➡️ Prepare Your Resume, LinkedIn, and Portfolio

Although your most valuable asset as you job search is your portfolio, you do have to cross your t’s and dot your i’s and when it comes to the job search that means optimizing your resume and LinkedIn profile. Tech employers expect you to have all three!

Check out these blog posts for more:

➡️ Build Your Network

Your net worth is in your network, which can be hard when you’re changing careers! But don’t worry, the tech industry is incredibly welcoming to newcomers. Whether you prefer in-person meetups, Slack channels, coffee-over-zoom chats, conferences, hack-a-thons or a little bit of everything, there are tons of opportunities for you to meet fellow techies.

Check out these blog posts for more:

➡️ Find Good Jobs To Apply For

A good job can be hard to find—or is it? The good news about tech is that there are so many openings at so many diverse companies that your biggest challenge will most likely be keeping up with all the opportunities!

Check out these blog posts for more:

➡️ Practice Interviewing

Whether you’re a season pro, or brand new to the tech industry: interviewing for a new job is tough! Add to that technical interviews…and you’ve got a recipe for heartburn, practically guaranteed. Luckily there’s an antacid on the market that works every time: practice. Read on for expert guidance on how to prepare for your next tech job interview.

Check out these blog posts for more:

➡️ Prepare for Technical Tests

Ah the dreaded technical test! Technical tests can come in many different forms: whiteboard tests, pair programming tests, take-home tests, algorithmic tests…just to name a few. Luckily, getting good at technical tests is a skill, just like anything else, and it’s one you can absolutely practice ahead of time.

Check out these blog posts for more:

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