MSOE Machine Learning Blog
Top Machine Learning Career Paths

Top Machine Learning Career Paths

Smiling woman sits at computer

Machine learning is one of the most rapidly growing fields in technology, with a global market that is predicted to grow to $209.91billion by 2029.1 This powerful technology has applications in a wide range of fields, from finance to healthcare to marketing and beyond. As a result, machine learning has opened up a wide range of career paths for individuals who are passionate about this technology.

Let’s explore what makes machine learning an exciting area of technology to pursue and take a look at some of the top machine learning career paths.

Why Pursue a Career in Machine Learning?

As a subfield of artificial intelligence (AI), machine learning involves the development of algorithms and statistical models that enable computers to learn from data and patterns in that data to make predictions or decisions. While the layman will not understand the technicalities of AI and machine learning, the rise of applications like Siri voice recognition and ChatGPT have brought this technology into the mainstream. Siri’s release in 2011 was one of the first popular machine learning applications that caught the interest of engineers in many other fields.2 Machine learning is transforming the way we approach complex problems and make decisions in the modern world, and those working in this area of technology will rise to meet these challenges.

For those looking to pursue a career in machine learning, the rapid growth of the field translates to a high demand for skills. As more companies adopt machine learning technology, there will be plenty of job opportunities, many which come with high salaries and pathways to career advancement. Because machine learning can be applied in so many areas, you can also factor in your interests and expertise as you choose your career path.

If you like excitement and challenges in your work, machine learning projects often involve working with large data sets and developing innovative solutions to complex problems. This can make for a highly rewarding career, as you have the opportunity to see your work make a real impact. This is also a career that promotes continuous learning, as machine learning is constantly evolving with new algorithms, techniques and applications. There is always something new to learn, which can make this career path highly stimulating and intellectually rewarding.

Types of Machine Learning Algorithms

You will not only find variety in the types of businesses that use machine learning, but you will also find variety in the types of machine learning algorithms, which include supervised learning, unsupervised learning, semi-supervised learning and reinforcement learning.3

Supervised learning: The algorithm is trained on labeled data, which means that the correct output is provided for each input. This algorithm then uses the training data to make predictions on new, unlabeled data.

Unsupervised learning: The algorithm is not provided with labeled data. Instead, it is given a dataset and must find patterns or relationships within the data on its own.

Semi-supervised learning: A combination of supervised and unsupervised learning, where the algorithm is given some labeled data and some unlabeled data to work with.

Reinforcement learning: Involves training an algorithm to make decisions based on feedback it receives from its environment. This type of learning is often used in robotics and game development.

These algorithms solve different problems and can handle a wide variety of tasks.3 Understanding the algorithms and how they can be used to provide insights and solutions to complex challenges can help you figure out where you’d like to apply your machine learning skills.

Careers in Machine Learning

Now that you have a better idea of the rewards that can come from a career in an in-demand field like machine learning, let’s explore your career options. Keep in mind that the base salaries listed are averages for the United States. Machine learning salary will vary by industry, location and experience-level.

Machine Learning Engineer

A machine learning engineer is responsible for designing and building machine learning systems. This includes selecting the appropriate algorithms, optimizing them for efficiency and accuracy, and integrating them into existing systems. Machine learning engineers often work closely with data scientists, software developers and other members of a product team to develop and deploy machine learning models in a variety of applications, such as natural language processing, computer vision and recommender systems. The average annual base salary for a machine learning engineer is $113,892.4

Data Scientist

Data scientists are responsible for analyzing and interpreting complex data sets to extract insights and inform business decisions. They use machine learning algorithms to uncover patterns in data and build predictive models. They also work closely with stakeholders to identify business problems and develop solutions to address them. A career in data science requires a strong foundation in mathematics, statistics and computer science. The base salary for a data scientist is $103,852 per year.5

Machine Learning Researcher

Machine learning researchers are responsible for developing new machine learning algorithms and techniques. They work in academia or industry to advance the state of the art in machine learning and artificial intelligence. Machine learning researchers typically have a PhD in computer science or a related field, and they have a deep understanding of the theoretical foundations of machine learning. The average annual base salary for this role is $118,500.6

AI Product Manager

An AI product manager is responsible for overseeing the development and deployment of artificial intelligence products. They work closely with cross-functional teams to develop product roadmaps, define product features and manage the development process. AI product managers must have a strong understanding of machine learning technologies, as well as excellent communication and project management skills. The base salary for an AI product manager is $130,792 per year.7

Data Engineer

Data engineers are responsible for building and maintaining the infrastructure that supports machine learning and data analysis. They design and build data pipelines, manage databases and ensure that data is accessible and reliable. Data engineers work closely with data scientists and machine learning engineers to ensure that data is available and usable for machine learning applications. The annual base salary for a data engineer is $96,548.8

Big Data Analyst

Big data analysts are responsible for analyzing and interpreting large data sets. They use machine learning algorithms to extract insights from data and develop predictive models. Big data analysts typically have a strong background in mathematics, statistics and computer science. The average annual base salary for this role is $82,304.9

Start On Your Machine Learning Career Path With MSOE

Machine learning offers a wide range of career paths. From machine learning engineers to AI product managers, there are many opportunities to build rewarding careers in this field. With the increasing demand for machine learning expertise across industries, there has never been a better time to pursue a career in machine learning.

Whether you start with the online Graduate Certificate in Machine Learning or jump right into the online Master of Science in Machine Learning, Milwaukee School of Engineering’s online programs will give you the essential machine learning skills that you need to succeed in this exciting field. Connect theory to application with a curriculum that focuses on hands-on learning.

Get started today. Complete the form for more information, or get started on your application.

Discover Your Next Step

This will only take a moment.

By clicking "Get Program Brochure" and submitting this form, I agree to receive text messages, emails and other communication regarding educational programs and opportunities, and to be contacted by Milwaukee School of Engineering and Everspring, its authorized representative. Message and data rates may apply. Message frequency varies. Reply HELP for help and STOP to cancel. View our privacy policy and disclosures.

MSOE and You: Better Together

Earn your master’s or certificate in machine learning online with MSOE. Complete the form to get a program details sheet for the program of your choosing—Master of Science in Machine Learning or Graduate Certificate in Applied Machine Learning—delivered to your inbox.

Admissions Dates and Deadlines

Priority Deadline
August 1
Fall 2024
Application Deadline
August 12
Fall 2024
Start Date
September 3
Fall 2024

Milwaukee School of Engineering has engaged Everspring, a leading provider of education and technology services, to support select aspects of program delivery.