Machine learning engineers are responsible for building artificial intelligence systems. This fascinating field of artificial intelligence involves creating models trained on datasets that can predict and adapt outcomes. The World Economic Forum’s Future of Jobs Report 2025 lists AI and machine learning specialists among the top three roles expected to grow the fastest between 2025 and 2030, with a global net growth rate of 82%. [1].
This article provides detailed information about machine learning engineers, including what they do, how much they earn, and how to become a machine learning engineer. If you’re ready to start preparing for a machine learning role today, consider enrolling in Microsoft’s AI & MLEngineering Professional Certificate. Throughout the program, you will build, deploy, and innovate with advanced machine learning techniques and real-world projects.
What is machine learning?
Machine learning is a subset of computer science and artificial intelligence that uses algorithms to learn from data in a way similar to how humans learn. The goal is to continually improve the learning accuracy of machines trained on datasets and slowly teach algorithms to perform specific tasks. [2].
Machine learning includes everything from video surveillance to facial recognition on smartphones. However, customer-facing companies also use it to understand consumer patterns and preferences and to design direct marketing and advertising campaigns.
Social media platforms like Meta use machine learning to serve ads to users based on their preferences, likes, and posts on websites. Similarly, shopping websites such as Amazon use algorithms to suggest products to purchase based on a customer’s purchase and browsing history. [3].
read more: 10 machine learning algorithms you need to know
What does a machine learning engineer do?
Machine learning engineers are important members of data science teams. Their duties include researching, building, and designing machine learning systems for artificial intelligence and maintaining and improving existing systems.
Machine learning engineers often also serve as key communicators among other data science team members, working directly with data scientists who develop models to build AI systems and with the people who build and run AI systems. Machine learning engineer job responsibilities vary by organization, but often include:
-
Implementing machine learning algorithms
-
Perform experiments and tests on AI systems
-
Machine learning system design and development
-
Performing statistical analysis
Job prospects for machine learning engineers
Over the past several decades, the field of computer science has continued to grow. According to the U.S. Bureau of Labor Statistics (BLS), research jobs in information and computer science are expected to grow 20% by 2034, much faster than the average for all occupations. [4].
Indeed ranks Machine Learning Engineer among the top 10 jobs in 2023, based on the growth in the number of jobs related to machine learning and artificial intelligence over the past three years. [5]. With the increasing capabilities of AI systems, the demand for greater automation of daily tasks has never been greater.
Machine learning engineer salary
Machine learning jobs are usually lucrative, with high salaries depending on experience and location. Like many high-tech and computer science jobs, machine learning engineers earn six-figure salaries. In fact, as of September 2025, the average base salary for a Machine Learning Engineer is $176,188, according to Indeed. [6].
How to become a machine learning engineer
It is possible to pursue a career in machine learning through several routes described below. First, let’s take a look at the three important steps required to become a machine learning engineer.
1. Earn a bachelor’s degree in computer science or a related field.
Machine learning is part of the computer science field, so a strong background in computer programming, data science, and mathematics is essential for success. Many machine learning engineering jobs require at least a bachelor’s degree, so starting a course of study in a closely related field such as computer science or statistics is a good first step.
You are currently on slide 1
2. Gain practical experience through entry-level machine learning engineer jobs.
Once you have a degree in computer science, the next step is to start working in data science and gain experience working with machine learning and artificial intelligence. Entry-level positions that can lead to a career in machine learning include:
3. Build machine learning expertise.
Expand your machine learning expertise by building a strong foundation in mathematics and programming while focusing on consistent hands-on practice through personal projects. Stay up to date with the latest research by following papers and joining the ML community, then gradually specialize in an area like deep learning or MLOps that aligns with your goals. Most importantly, you’ll work on end-to-end projects that cover the entire pipeline from data collection to deployment, and network with other practitioners to accelerate your learning and discover new opportunities.
For example, you can consider enrolling in DeepLearning.AI’s PyTorch for Deep Learning Professional Certificate program. Learn how to optimize model accuracy, performance, and deployment efficiency in just two months.
Do I need an advanced degree to become a machine learning engineer?
While it’s possible to work in data science or artificial intelligence with a bachelor’s degree, a master’s degree in computer science, data science, or software engineering can teach you the more complex tasks required of a machine learning engineer. It will also give you an advantage when applying for jobs, especially if you have enhanced your learning with extensive industry experience, such as an internship or apprenticeship.
Explore free machine learning career resources
Career Chat is Coursera’s weekly LinkedIn newsletter featuring trending skills, tools, and certifications to discover your next step in machine learning. Check out other free digital resources to learn key machine learning concepts and hear from industry experts.
Accelerate your career growth with a Coursera Plus subscription. Sign up for monthly or yearly options and gain access to over 10,000 courses.
