7 Machine Learning Roles and How to Get Started

Important points

Machine learning (ML) is a branch of artificial intelligence that performs a variety of jobs in engineering, computer science, data science, and more.

• There are several machine learning roles available, one of which is that of a machine learning engineer, which has an average annual salary of $161,000. [1].

• The machine learning category includes supervised, unsupervised, and semi-supervised machine learning.

• Earning a degree in a subject such as computer science, engineering, or programming can qualify you for a machine learning role.

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What is machine learning?

Machine learning is a branch of artificial intelligence (AI) that focuses on helping AI mimic the way humans learn through various algorithms. ML is primarily based on mathematics and can process large amounts of data. ML uses this data to help make AI more human-like. The three categories of machine learning are:

Seven roles of machine learning

Learn more about seven machine learning roles, including average salary, job outlook, requirements, daily responsibilities, and more below.

*All salary information represents median total salary from Glassdoor as of April 2026. These numbers include base salary and any additional pay that represents profit sharing, commissions, bonuses, or other compensation.

machine learning engineer

Average annual income in the US: $161,000 [1]

Employment outlook (growth forecast from 2024 to 2034): 20 percent [2]

Requirements: To become a machine learning engineer, you need a strong background in statistics and mathematics. You should be proficient in programming languages ​​such as C++, Python, and Java and have a solid understanding of computer programming.

responsibility: Machine learning engineers are programmers who develop AI systems, especially machine learning systems. As an ML Engineer, you will have a wide range of responsibilities related to the system building process, including organizing data, running tests, and optimizing systems.

data scientist

Average annual income in the US: $155,000 [3]

Employment outlook (growth forecast from 2024 to 2034): 34 percent [4]

Requirements: Many data scientist employers require at least a bachelor’s degree in a field such as statistics, data science, computer science, or mathematics. It is essential to have experience working with different types of data, knowledge of big data platforms such as Apache Spark, Kafka, Hadoop, and programming languages ​​such as R, Python, and SQL.

responsibility: Data scientists are responsible for collecting, organizing, and analyzing data to gain valuable insights. Depending on your organization, your responsibilities may also include creating data visualizations and developing statistical models.

AI engineer

Average annual income in the US: $142,000 [5]

Employment outlook (growth forecast from 2024 to 2034): 20 percent [2]

Requirements: Many AI engineers have a bachelor’s degree in an AI-related field such as data science, computer science, information technology, or statistics. You also need a good understanding of mathematics and experience using programming languages ​​such as Python, C++, Java, and R.

responsibility: AI engineers are responsible for developing, programming, and training AI models. AI engineers are essential to creating, implementing, and running AI models.

software engineer

Average annual income in the US: $149,000 [6]

Employment outlook (growth forecast from 2024 to 2034): 7 percent [7]

Requirements: A typical entry-level requirement for a software engineer is a bachelor’s degree in computer science, software engineering, or a related field. A working knowledge of programming languages ​​such as Python, C++, Java, and at least familiarity with Linux/Unix, Perl, Shell, and SQL is essential.

responsibility: Software engineers are responsible for designing and building software solutions for everything from computer games to business applications to network control systems.

software developer

Average annual income in the US: $122,000 [8]

Employment outlook (growth forecast from 2024 to 2034): 15 percent [9]

Requirements: Software developers typically need at least a bachelor’s degree in a related field, such as computer science or engineering. You must also be able to write code and have a working knowledge of programming languages.

responsibility: Software developers aim to find the right program or code for the project they are working on. For some companies, this may include writing the code yourself.

business intelligence developer

Average annual income in the US: $132,000 [10]

Employment outlook (growth forecast from 2024 to 2034): 15 percent [9]

Requirements: Business intelligence (BI) developers have at least a bachelor’s degree in computer science or a related field.

responsibility: Business intelligence developers work with companies to develop and maintain business interfaces. You probably work with a team that includes data scientists and data engineers and have a deep understanding of the industry in which you work.

computational linguist

Average annual income in the US: $131,000 [11]

Employment outlook (growth forecast from 2024 to 2034): 20 percent [2]

Requirements: A bachelor’s degree in computer science is not always necessary, but it is advantageous when looking for a job as a computational linguist.

responsibility: Computational linguists use models to improve human language processing. This may include researching, creating, and maintaining these models.

How to get started with machine learning

Learn about the different education, certifications, and experience you need to build a career in machine learning.

education

Although not required, many machine learning professionals find it helpful to have a bachelor’s or master’s degree in a field such as computer science and programming, engineering, mathematics, data science, or statistics. A degree in one of the above fields indicates that you have at least a basic knowledge of the subject matter required to perform the job you are applying for.

If you don’t have a bachelor’s degree in a related field, it may be beneficial to obtain an educational certificate in the role you want to fill. For example, graduate certificates in computational linguistics, data science, and applied machine learning are available from a variety of universities.

read more: Machine learning for education: Transforming teaching and learning

certification

Machine learning jobs often require some knowledge of programming languages ​​and big data platforms. Certifications are a great asset in demonstrating your professional understanding of various programming languages ​​such as Python, SQL, C++, and Java.

experience

Many machine learning roles have entry-level options, which are often used by new graduates. Therefore, while experience is not necessarily required to land a job, it can enhance your resume. Internships can also help you demonstrate your ability to apply your education to a professional environment.

Explore free machine learning resources

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