Machine learning engineers work with algorithms, data, and artificial intelligence. Learn about salary potential, job outlook, and steps to becoming a machine learning engineer.
Machine learning engineers are responsible for building artificial intelligence systems. This fascinating branch of artificial intelligence involves creating models trained on data sets that can predict and adapt to outcomes. The demand for machine learning professionals has grown exponentially in recent years, with the World Economic Forum (WEF) predicting job openings will grow by 40% by 2027 [1].
In this article, you'll learn more about machine learning engineers, including what they do, how much they earn, and how to become one. Afterward, if you're interested in pursuing this impactful career path, you might consider enrolling in Microsoft's AI & Machine Learning Engineering Professional Certificate. Throughout the program, you'll build, deploy, and innovate with advanced machine-learning techniques and real-world projects.
Machine learning is a subset of computer science and artificial intelligence that uses algorithms to learn from data in a manner not dissimilar to how humans learn. The goal is for the machine to successively improve its learning accuracy as it's trained on data sets, which slowly teach the algorithm to perform a specific task [2].
Machine learning includes everything from video surveillance to facial recognition on your smartphone. However, customer-facing businesses also use it to understand consumers' patterns and preferences and design direct marketing or ad campaigns.
Social media platforms like Meta use machine learning to target advertisements at users based on their preferences, likes, and posts to the website. Similarly, shopping websites like Amazon use algorithms to suggest items to buy based on a customer's purchases and viewing history [3].
Machine learning engineers are critical members of the data science team. Their tasks involve researching, building, and designing machine learning systems for artificial intelligence and maintaining and improving existing systems.
Often, a machine learning engineer will also serve as a critical communicator between other data science team members, working directly with the data scientists who develop the models for building AI systems and the people who construct and run them. While job responsibilities for machine learning engineers will differ from one organizations to another, they often include:
Implementing machine learning algorithms
Running AI systems experiments and tests
Designing and developing machine learning systems
Performing statistical analyses
Over the past few decades, the computer science field has continued to grow. According to the US Bureau of Labor Statistics, information and computer science research jobs will grow 26 percent through 2033, which is much faster than the average for all occupations [4].
Indeed ranked machine learning engineer in the top 10 jobs of 2023, based on the growth in the number of postings for jobs related to the machine learning and artificial intelligence field over the previous three years [5]. Due to the increasing capability of AI systems, the demand for enhanced automation of routine tasks is at an all-time high.
Machine learning professions are typically lucrative careers, earning high salaries depending on their experience and location. Like many high-level technology and computer science jobs, machine learning engineers earn salaries in the six figures. In fact, as of January 2025, the average base salary for a machine learning engineer is $162,297, according to Indeed [6].
It's possible to obtain a career in machine learning through several paths discussed below. First, let's examine the three essential steps you'll need to take to become a machine learning engineer.
Because machine learning is part of the computer science field, a strong background in computer programming, data science, and mathematics is essential for success. Many machine learning engineering jobs require a bachelor's degree at a minimum, so beginning a course of study in computer science or a closely related field such as statistics is a good first step.
Once you have earned a computer science degree, the next step is to start working in the data science field to gain experience working with machine learning or artificial intelligence. Some entry-level positions that can lead to a machine learning career include:
While working in a related role, you can build specialized knowledge and strengthen your skill set. Consider enrolling in relevant machine learning programs and certificates to keep expanding. Here are a few recommendations to get started:
While it is possible to work in data science and artificial intelligence with a bachelor's degree, pursuing a master's degree in computer science, data science, or software engineering can help you learn the more complex tasks required of machine learning engineers. It will also give you leverage as you apply for jobs, especially if you have bolstered your studies with plenty of industry experience, such as internships or apprenticeships.
Artificial intelligence and machine learning are growing fields. Build the skills you need to enter this in-demand career with one of the following courses on Coursera:
To develop practical machine learning skills, try DeepLearning.AI and Stanford's Machine Learning Specialization. In this beginner-friendly program, you'll learn to build ML models, apply best practices for ML development, and even build and train your own neural network to perform multi-class classification.
To prepare for a career as a machine learning engineer, enroll in the Microsoft AI & ML Engineering Professional Certificate. In this intermediate-level program, you'll design and implement AI and ML infrastructure, master machine learning algorithms and techniques, and create your own AI-powered agent.
For a deep dive into AI engineering, take IBM's AI Engineering Professional Certificate. In as little as three months, you'll learn the fundamentals of AI, deploy machine learning algorithms, and build deep learning models and neural networks.
WEF. "Future of Jobs Report 2023, https://www3.weforum.org/docs/WEF_Future_of_Jobs_2023.pdf." Accessed February 3, 2025.
IBM. "Machine Learning, https://www.ibm.com/cloud/learn/machine-learning." Accessed February 3, 2025.
Big Commerce. "Ecommerce Machine Learning: AI’s Role in the Future of Online Shopping, https://www.bigcommerce.com/blog/ecommerce-machine-learning/." Accessed February 3, 2025.
US Bureau of Labor Statistics. "Computer and Information Research Scientists, https://www.bls.gov/ooh/computer-and-information-technology/computer-and-information-research-scientists.htm." Accessed February 3, 2025.
Indeed. "Best Jobs of 2023, https://www.indeed.com/career-advice/news/best-jobs-of-2023." Accessed February 3, 2025.
Indeed. "Machine Learning Engineer Salary in United States, https://www.indeed.com/career/machine-learning-engineer/salaries." Accessed February 3, 2025.
Editorial Team
Coursera’s editorial team is comprised of highly experienced professional editors, writers, and fact...
This content has been made available for informational purposes only. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
Take your skills to the next level with expert-led courses and Coursera Coach, your AI-powered guide.
Earn recognized credentials from top companies like Meta, Google, Microsoft, and more.
These cookies are necessary for the website to function and cannot be switched off in our systems. They are usually only set in response to actions made by you which amount to a request for services, such as setting your privacy preferences, logging in or filling in forms. You can set your browser to block or alert you about these cookies, but some parts of the site will not then work.
These cookies may be set through our site by our advertising partners. They may be used by those companies to build a profile of your interests and show you relevant adverts on other sites. They are based on uniquely identifying your browser and internet device. If you do not allow these cookies, you will experience less targeted advertising.
These cookies allow us to count visits and traffic sources so we can measure and improve the performance of our site. They help us to know which pages are the most and least popular and see how visitors move around the site. If you do not allow these cookies we will not know when you have visited our site, and will not be able to monitor its performance.
These cookies enable the website to provide enhanced functionality and personalization. They may be set by us or by third party providers whose services we have added to our pages. If you do not allow these cookies then some or all of these services may not function properly.