Machine learning engineers work with algorithms, data, and artificial intelligence. Learn about salary potential, job outlook, and steps to becoming a machine learning engineer.
Are you interested in becoming a machine learning engineer but unsure where to begin? While this role isn't an entry-level tech job, the career path to becoming a machine learning engineer can be an exciting and rewarding one.
Machine learning is a fascinating branch of artificial intelligence that involves predicting and adapting outcomes as more data is received. The demand for machine learning professionals has also grown exponentially in recent years. Recognized as the fifth most in-demand job of 2023, machine learning engineers have become highly sought-after by employers [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 IBM's AI Engineering Professional Certificate and start building job-relevant skills today.
Machine learning is a part of the computer science field specifically concerned with artificial intelligence. It uses algorithms to interpret data in a way that replicates how humans learn. The goal is for the machine to improve its learning accuracy and provide data based on that learning to the user [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].
Learn more about the real-world applications of machine learning in this lecture from Stanford and DeepLearning.AI's Machine Learning Specialization:
Read more: Is Machine Learning Hard? A Guide to Getting Started
Machine learning engineers act as critical members of the data science team. Their tasks involve researching, building, and designing the artificial intelligence responsible for machine learning and maintaining and improving existing artificial intelligence 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, 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 23 percent through 2032, which is much faster than the average for all occupations [4].
Indeed ranks 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 changes in society because of the COVID-19 pandemic, the need for enhanced automation of routine tasks is at an all-time high.
Machine learning professions are typically lucrative careers. Like many high-level technology and computer science jobs, machine learning engineers earn salaries significantly above the national average, often over six figures. In fact, as of March 2024, the average base salary for a machine learning engineer is $162,740, 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 experience to prepare you for machine learning engineering. Consider working on machine learning projects to practice essential skills or earning relevant certifications. Here are a few recommendations for getting started:
Build a Machine Learning Web App with Streamlit and Python (Guided Project)
Unsupervised Machine Learning for Customer Market Segmentation (Guided Project)
Cervical Cancer Risk Prediction Using Machine Learning (Guided Project)
While it is possible to work in data science and artificial intelligence with a bachelor's degree, pursuing a Ph.D. or 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 branches of computer and data science. Becoming a machine learning engineer requires years of experience and education, but you can start today.
Build your knowledge of software development, learn various programming languages, and work towards an initial bachelor's degree. A variety of certificates and even computer science degree pathways on Coursera can help prepare you for an exciting career in the machine learning field.
The machine learning specialization from Stanford University and DeepLearning.AI is another great introduction to machine learning, in which you'll learn all you need to know about supervised and unsupervised learning.
LinkedIn. "Humans Only: The Rising Demand for Machine Learning Engineers, https://www.linkedin.com/pulse/humans-only-rising-demand-machine-learning-engineers-michiel-klompen." Accessed March 19, 2024.
IBM. "Machine Learning, https://www.ibm.com/cloud/learn/machine-learning." Accessed March 19, 2024.
Big Commerce. "Ecommerce Machine Learning: AI’s Role in the Future of Online Shopping, https://www.bigcommerce.com/blog/ecommerce-machine-learning/." Accessed March 19, 2024.
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 March 19, 2024.
Indeed. "Best Jobs of 2023, https://www.indeed.com/career-advice/news/best-jobs-of-2023." Accessed March 19, 2024.
Indeed. "Machine Learning Engineer Salary in United States, https://www.indeed.com/career/machine-learning-engineer/salaries." Accessed March 19, 2024.
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