Machine Learning Engineer Salary: What’s Your Earning Potential?

The launch of ChatGPT in January 2023 put machine learning (ML) on the public’s radar, but this technology has been part of our daily lives for quite some time. Take Spotify, for example. This popular streaming service uses machine learning to offer personalized recommendations and curated playlists.¹ In the business world, professionals use ML for everything from building predictive models to tracking inventory.²

A 2024 McKinsey survey found that 72% of businesses have embraced artificial intelligence solutions.³ As more organizations adopt this technology, the demand for skilled machine learning engineers has surged.

If you’re considering a career in this growing field, you’re probably wondering, “How much do machine learning engineers make?” Several factors influence ML salaries, including level of education and geographic location. This article explores salary data, industry trends, and strategies for increasing your earning potential.

What Does a Machine Learning Engineer Do?

A machine learning engineer is just one of many careers in machine learning. ML engineers design, develop and deploy artificial intelligence and machine learning systems. These engineers build and train models that can learn from data and make predictions or decisions. Their work spans a wide range of applications, including natural language processing, computer vision and predictive modeling.⁴

Machine learning engineers utilize programming languages such as Python, R and Julia to handle large datasets and develop complex models that enhance machine learning capabilities. They possess a deep understanding of computer science, mathematics, and statistics, which allows them to create sophisticated machine learning algorithms and deep learning frameworks. Their role often involves close collaboration with data scientists, software engineers, and other stakeholders to design and build systems that efficiently integrate and utilize machine learning models.

What Is the Average Machine Learning Engineer Salary? 

According to Indeed, the average machine learning engineer salary in the U.S. is $160,313. Entry-level positions start at $100,702, while high earners can make $255,208.⁵

Wages vary based on many factors, including:

• Certifications 
• Education
• Experience
• Industry
• Location 
• Size of company 
• Skills 

Job Outlook 

The job outlook for machine learning engineers is promising. According to the U.S. Bureau of Labor Statistics, the field of computer and information research scientists, which includes machine learning engineers, is projected to grow by 26% (much faster than average) between 2023 and 2033.⁶ This surge is fueled by the increasing demand for artificial intelligence and machine learning across various industries, including tech, finance and healthcare.

Machine Learning Engineer Salary by Experience Level 

It’s normal for machine learning engineers to take on more challenging responsibilities as they gain experience. As a result, senior workers often command higher salaries than beginners who are still learning the ropes. Senior machine learning engineers, in particular, benefit from deep technical expertise, which, combined with strategic thinking and leadership skills, allows them to develop innovative ML models, mentor others and align machine learning projects with broader business goals.

Based on Glassdoor data, here’s the average ML engineer salary at various career stages:⁷

• Entry-level (up to one year): $133,000 
• Junior (one to three years): $152,000
• Mid-level (four to six years): $170,000
• Senior (seven to nine years): $190,000

Expanding your expertise could help you climb the pay scale more quickly or transition onto a new career path.

Say, for instance, you volunteer to lead a team and develop project management experience. This experience could help you land a higher-paying leadership position, such as AI strategy director or head of machine learning.⁸

The Role of Education in Determining Salary 

Employers also take education into account when they make a salary offer.

According to Salary.com, 44% of machine learning engineers hold a master’s degree, and these professionals earn an average salary ranging from $123,271–$129,503.⁹

Certifications from professional organizations count as education and can influence your salary, too. Here are three reputable options to consider:

• Amazon Web Services (AWS) Certified Machine Learning–Specialty: demonstrates proficiency in designing, training, and improving ML solutions in the AWS Cloud¹⁰ 
• Google Cloud Professional Machine Learning Engineer: focuses on developing and deploying ML applications using Google Cloud¹¹
• IBM Machine Learning Professional Certificate: validates expertise in foundational machine learning concepts, such as deep learning, clustering techniques, and feature engineering¹²

Geographic Location and Remote Work Opportunities

Location plays a significant role in determining a machine learning engineer’s salary as well. Two professionals living on opposite sides of the country could earn drastically different wages, even while performing the same job duties.

According to ZipRecruiter, these are the highest-paying states for machine learning engineers in the U.S., along with their average salaries:¹³

• New York: $146,875
• Vermont: $144,629
• Pennsylvania: $134,505
• Washington: $132,161
• New Hampshire: $131,346 

On the other hand, the lowest-paying states for machine learning engineers include:¹³

• West Virginia: $103,880
• Kentucky: $103,501
• Michigan: $103,380
• Florida: $98,840
• Arkansas: $98,289

Of course, it’s important to note that the cost of living can vary significantly from state to state. While a machine learning engineer in Arkansas might earn less on paper than one in a higher-paying state, their overall expenses could be much lower. As a result, the Arkansas professional could enjoy a comparable or even higher quality of life.

Some machine learning engineers boost their earning potential by seeking remote work opportunities with companies based in regions with higher salaries. This strategy gives them the best of both worlds: competitive pay without the financial stress of living in a high-cost-of-living area.

How to Maximize Your Earning Potential 

Upskilling is one of the most effective ways to boost your earning potential by offering more value to employers. This process may involve learning new programming languages, machine learning techniques, and tools.

Boot camps can help you quickly develop new machine learning skills. These intensive programs focus on helping students develop a portfolio and gain job-ready skills. They typically cover data analytics, deep learning, prompt engineering and other foundational machine learning concepts.

Degrees are another viable way to level up your skills. These formal education programs have structured curricula and are led by experienced faculty. They may also offer networking opportunities, such as internships and meetings with top employers. These events allow you to make connections and exchange knowledge.

Free online resources can accelerate your career growth, too. Many websites offer coding exercises and tutorials for C++, Python and other programming languages that are commonly used in machine learning.¹⁴

You could also participate in discussions about machine learning on online forums such as the subreddit "r/machinelearning" and Stack Overflow. These boards let you ask questions, swap tips and get advice from your peers.

Specialization and Niche Skills

Machine learning engineers can specialize in various high-demand areas, such as deep learning, natural language processing and computer vision. Developing niche skills in areas like reinforcement learning, transfer learning and generative models can significantly enhance a machine learning engineer’s salary and job prospects.

For instance, a machine learning engineer specializing in natural language processing might work on developing chatbots, voice recognition software or language translation tools.¹⁵ Meanwhile, those focusing on computer vision could be involved in creating image recognition systems, object detection algorithms or facial recognition technologies.

Beyond technical expertise, machine learning engineers benefit from honing soft skills such as communication, collaboration and project management. These skills are crucial for working effectively with cross-functional teams and conveying complex technical concepts to non-technical stakeholders.

Maximize Your Machine Learning Career With an Online Program From MSOE

Like most professions, machine learning doesn’t have a fixed pay scale. Many factors can affect your salary as a machine learning engineer, from your education to where you live.

Continuous learning is the key to growing your knowledge and boosting your machine learning engineering salary. The Milwaukee School of Engineering’s online machine learning programs can help accelerate your career growth.

MSOE offers two flexible online programs: the online Graduate Certificate in Applied Machine Learning and the online Master of Science in Machine Learning. If you enroll in the certificate program, the credits you earn will count toward the full master’s degree. This pathway lets you dip your toes in machine learning and decide whether you want to continue your education later.

No matter which path you choose, you’ll sharpen your skills as you complete AI Tools and Paradigms, Applied Machine Learning and other rigorous courses. In each class, you’ll receive personal mentorship from our dedicated faculty and gain hands-on experience by completing projects.

Get started on your application or explore our admissions requirements.