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How to Become a Machine Learning Engineer


How to Become a Machine Learning Engineer

Machine learning has been in the news lately, and it’s hard to ignore. This variety of data science is a growing form of artificial intelligence that captures the interest of many professionals and businesses across the country. Recently, machine learning finally reached a point of reliability and economic viability. It is beginning to permeate startups and businesses alike, creating countless opportunities for data science professionals. Here’s everything you need to know before becoming a machine learning engineer.

Here are some basic facts about information sciences and the machine learning career path:

The Bureau of Labor Statistics predicts a 16% increase in information science, data science, machine learning, and related jobs by 2028. That’s over three times faster than the 5.2% national average.

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According to Glassdoor, the average salary for machine learning engineers is $114,121 per year.

Machine learning engineers fall under the data and information scientist career category.

Average Salary
Hiring Companies

Machine learning is a form of artificial intelligence. Essentially, machine learning professionals teach computer programs how to learn on their own. This form of artificial intelligence involves coaching machines to recognize patterns and predict future results based on what they learned from previous trends. Obviously, it’s more complicated than that—but the basic concept is relatively easy to grasp.

Machine learning engineers design systems that use artificial intelligence to make predictions and detect patterns. Engineers design algorithms to, in essence, ‘learn’ from historical data. Machine learning engineering is a complex task with plenty of innovation due to the recent development of this technology.

Machine Learning Job Description

Machine learning engineers use high-level programming languages and data science skills to design (and operate) algorithms. These professionals need data science skills to create systems that ‘learn’ from data, and to utilize databases to streamline the process. Here are some key tasks of machine learning engineers:

Designing and developing algorithms

Developing deep learning systems

Working with databases and large data sets

Maintaining, upgrading, and modifying existing systems

Machine learning engineers focus less on analytics than other data science roles. Instead, these professionals are behind the technical aspects of programs that other data experts use. Machine learning engineers use their technical skills to increase the efficiency of new technologies.

Data science is a highly technical field that requires lots of well-refined skills. You need to approach your education with intentionality and planning to succeed in the field. Here are the most important skills required for a career in data science:


Machine learning engineers rely on engineering practices—many of which require strong mathematical skills. The field also requires statistical knowledge. Mathematical abilities are essential to many operations performed by engineers.


Algorithms are a big part of machine learning. Machine learning engineers should have an in-depth theoretical and practical understanding of algorithms. Algorithms are also a big part of other artificial intelligence-based careers.

Programming Languages

Programming is the foundation of machine learning. As a result, these professionals must be skilled in languages such as Python, R, and sometimes C. Coding skills come from self-study, college, or coding bootcamps.

Machine learning has the potential to revolutionize technology in the 2020s. Since the technology has only recently become commercially viable, machine learning professionals earn high salaries for their specialized skills. Here are the average salaries for machine learning engineers across several major American metropolitan areas:

CityAverage SalaryEntry-Level SalaryMid-Career SalaryLate-Career Salary
Atlanta, GA$89,469$64k$89k$115k
Boston, MA$105,749$76k$106k$134k
Chicago, IL$94,045$68k$94k$120k
Cleveland, OH$85,395$60k$85k$109k
Dallas, TX$91,839$66k$92k$117k
Los Angeles, CA$101,267$73k$101k$132k
Miami, FL$88,418$63k$88k$113k
Milwaukee, WI$87,490$63k$87k$111k
Minneapolis, MN$93,558$67k$94k$119k
New York, NY$118,604$86k$119k$149k
Philadelphia, PA$93,496$67k$93k$119k
Phoenix, AZ$88,452$62k$88k$113k
Portland, OR$95,728$68k$96k$120k
San Francisco, CA$136,289$102k$136k$171k
Seattle, WA$126,477$93k$126k$160k

Data science is a complex field that requires a high level of technical skill. Predictably, the field offers high salaries to anyone willing to put in the work and learn the trade.

  • Mean Annual Salary: $114,121
  • Projected Job Growth Outlook (2018-28): 16%
  • Number of People Employed: 31,000

Machine learning engineers use algorithms, engineering principles, and programming languages to build artificial intelligence systems.

  • Mean Annual Salary: $124,567
  • Projected Job Growth Outlook (2018-28): 16%
  • Number of People Employed: 140,000

Data scientists use programming languages, statistical skills, and algorithms to manage and interpret large data sets.

  • Mean Annual Salary: $62,435
  • Projected Job Growth Outlook (2018-28): 26%
  • Number of People Employed: 109,000

Business administration requires a healthy level of analysis. Among all job titles, none serve this need better than business analysts. These professionals solve business problems, and serve the role of ‘trend finders’ within a company. 

  • Mean Annual Salary: $62,435
  • Projected Job Growth Outlook (2018-28): 26%
  • Number of People Employed: 109,000

Data analysts use coding languages, frameworks, and data visualization tools to transform large volumes of non-descript data into useful and actionable information.

Entry Level (0-4 Years)$78,000
Mid-Career (5-10 Years)$114,121
Experienced (10-20 Years)$125,000
Late-Career (20+ Years)$150,000

Generally speaking, data scientists earn an impressive salary, especially when bonuses and additional cash compensation count with the total. Today, data scientists earn an average total income of $146,937, with some professionals grossing nearly $200,000 per year.

The Types of Machine Learning Engineers

Machine learning is a new field, and there aren’t a lot of job title variances just yet. As a result, the most common positions in the field are machine learning and artificial intelligence engineers. These programmers have varied responsibilities, but fundamentally work with similar systems.

Machine Learning Engineer

Machine learning engineers work with programming languages such as Python and data science skills to create algorithms, build machine learning programs, and create deep learning systems. Machine learning is a data-centric field.

Artificial Intelligence Engineer

Artificial intelligence (or AI) engineers work with various forms of artificial intelligence. These professionals also use programming languages like Python, along with algorithms and other machine learning processes.

Machine learning engineers usually start off as data scientists. Many companies promote data scientists into machine learning positions or hire them outright for the job. Professionals with a background in software engineering hold an advantage in the field. Some colleges and coding bootcamps offer dedicated machine learning programs or other courses with a specialty in artificial intelligence. Here are the top ways to become a machine learning engineer:

College or University

Numerous machine learning engineers have a college background. Most of these professionals started off in computer science, software engineering, or an analytical STEM field. Others are self-taught and have a background in business or a similar subject.

Coding Bootcamp

Coding bootcamps are dedicated technology degree training programs. These schools, which often last less than a year, are the fastest route into a machine learning job. Many bootcamps offer job guarantees and placement assistance throughout the program.


Coding Bootcamps

Bootcamps strike a balance. While they will not provide the same comprehensive education that a four year degree will, they will provide you with on the ground, practical training to get you into software engineering as quickly as possible.  Coding bootcamps cost an average of $13,600 for a full-time education. These programs run between 3 months and 1 year, but schedules vary widely. Full-time programs are available, as are part-time and online programs in all shapes and sizes. Additionally, students can attend bootcamps for other tech careers including web development, data science, cybersecurity, and more. Software engineering is an amazing career. Getting to design entire complex systems that function in unison with other systems like cogs in a giant machine is deeply appealing to many. If it’s appealing to you then don’t wait. Start learning now, and enter a field where cutting edge is the norm.  

  • Duration: 1 to 5 years
  • Cost: $0 (or minimal)
  • Average Base Salary: Unknown
  • Duration: 3 to 12 months
  • Cost: Avg. $13,600
  • Average Base Salary: $70,700
  • Duration: 4 to 6 years
  • Cost: Avg. $34,740 (4 years)
  • Average Base Salary: $65,900
  • Duration: 1.5 to 2 years (in addition to Bachelor’s Degree)
  • Cost: Avg. $30,000 to $100,000 (in addition to Bachelor’s Degree)
  • Average Base Salary: $114,000
  • Duration: 4 to 8 years (in addition to Bachelor’s Degree)
  • Cost: Avg. $50,000+ (in addition to Bachelor’s Degree)
  • Average Base Salary: $124,000

Coding Bootcamp

Coding bootcamp is a new arrival to the world of higher education. These career training programs are designed to cover the curriculum students need for a software engineering career, without the additional classes or added expense levied by university. Bootcamps are a proven way into tech, with some programs reporting job placement rates in excess of 90%. Bootcamps generally run between three months and a year, and are available full-time, part-time, and online.


College is the traditional route into a software engineering career. Students often receive a bachelor’s degree in computer science or software engineering (where available). These students sometimes go onto graduate school and attain higher degrees, though it’s not necessary to enter the industry. College, while once the primary route into a software engineering career, isn’t the only way to get in. These days, other programs such as coding bootcamps now offer a fairly direct path into the same jobs once held exclusively by college graduates.


Some software engineers are self-taught, learning how to code online and from books. For some people, this method works—but often requires a hefty portfolio to prove that the candidate can do what they claim to. Thankfully, freelance positions and personal projects are a good way to demonstrate abilities


Will coding bootcamp help me get a job?

Absolutely! Coding bootcamp is a proven way to train for a job in tech. Many coding bootcamps offer job guarantees, and some refund tuition if graduates can’t find a job in the field they trained for. In fact, coding bootcamp teaches skills that many college computer science graduates lack.

How much do coding bootcamps cost?

Coding bootcamp tuition varies. Coding bootcamps in New York City cost around $10,000 to $20,000. However, many scholarships and tuition deferment programs are available, so what you see doesn’t have to be what you pay.

What are income share agreements?

Income share agreements, or ISAs, are a new way to pay for education. These programs defer tuition until after students graduate and find a job in the industry. Once students are employed and making above a certain income threshold (usually $40-60,000 per year) they begin paying a fixed percent of their income, often for around 2 years. If students can’t find a job, many bootcamps waive the cost of tuition.

Do I have to learn coding to work in the tech industry?

You don’t have to learn coding to work in the tech industry. In fact, there are several non-coding bootcamps in New York City. These programs train you for a position in tech sales, marketing, or product management–all of which are well-paid positions with plenty of advancement opportunity.


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