Key Takeaways
- ✓PayScale reports an average salary of $102,848 for workers with a Master of Science in Artificial Intelligence, but salary can vary widely by role, specialization, location, employer, and experience.
- ✓Artificial intelligence engineers, research scientists, senior data scientists, and machine learning engineers are common higher-paying roles for AI master’s graduates.
- ✓Technical skills in machine learning, robotics, computer vision, Python, Java, R, Apache Spark, cloud platforms, TensorFlow, and PyTorch can strengthen salary potential.
- ✓A master’s in artificial intelligence is usually an advanced computer science degree for students who want to build, deploy, or research AI systems.
- ✓Students comparing ROI should evaluate not only salary outcomes, but also prerequisites, curriculum fit, program cost, location, employer access, and long-term career goals.
It’s hard to go through a day without touching apps built in the early stages of artificial intelligence: from personalized content streams online, to the weather report, to the logistics that bring your Amazon order to your doorstep, AI is becoming a constant partner.
According to Bloomberg, this influence will only grow in the future. Citing a Zion Market Research study, Bloomberg reported that the global AI market, then valued at $59.67 billion, was projected to grow at a compound annual growth rate of 39.4% to $422.37 billion by 2028.
This growth is attracting vast numbers of entrants into AI master’s programs, with many universities in turn expanding their AI capacities. According to Stanford’s AI Index, 73 leading universities reported increasing graduate offerings teaching practical AI skills by over 40% during the four academic years leading up to 2020, with faculty specializing in AI growing by almost 60% over the same timeframe.
Entrants to these programs cite not only a booming job market but extremely high salaries as reasons for matriculating — but how much can you expect to earn with a master’s in artificial intelligence? In this article, we’ll break down expected compensation for a variety of advanced artificial intelligence jobs before providing some background on how you can start down the path to earning your own.
If you are still comparing education options, AIFwD also maintains guides to master’s in artificial intelligence, online master’s in artificial intelligence, artificial intelligence careers, artificial intelligence engineer careers, and how to become a machine learning engineer.
“A master’s in artificial intelligence can support high-paying AI roles, but salary depends heavily on the specific job, skills, employer, and market.”— AIFwD Editorial Staff
What Salary Can You Expect With a Master’s in Artificial Intelligence?
According to PayScale%2C_Artificial_Intelligence/Salary), the average salary for someone holding a master’s degree in artificial intelligence is $102,848 — but the actual salary for AI professionals varies depending on several factors, including job title, specialization, location, and employer.
Based on PayScale’s data, the jobs with the highest paying AI salaries include artificial intelligence engineers, research scientists with AI skills, senior data scientists, and machine learning engineers. Those roles can overlap in practice, and job titles may vary by company, but they are useful benchmarks for students researching the possible return on an AI master’s degree.
- 1.
Artificial intelligence engineers
Artificial intelligence engineers reportedly earn an average of $171,715, with top earners in the same profession earning upwards of $257,530 in annual salary. Many professionals doing this work may also appear under titles like machine learning engineer, AI specialist, software engineer, robotics engineer, or business intelligence developer.
- 2.
Research scientists
Research scientists with AI skills reportedly earn an average base salary of $134,456. These roles may appear in industry labs, medical research groups, universities, and applied research teams.
- 3.
Senior data scientists
Senior data scientists reportedly earn an average base salary of $117,438 and up to $150,000. Data science is not always classified as a subdiscipline of artificial intelligence, but it often overlaps with machine learning, predictive analytics, and business decision systems.
- 4.
Machine learning engineers
Machine learning engineers earn an average base salary of $106,055 and up to $150,000. These professionals typically design, develop, deploy, test, and maintain machine learning systems in production environments.
Factors That Affect Your Salary With an MS in Artificial Intelligence
A master’s degree can be one part of the salary equation, but it is not the only factor employers consider. Compensation for AI jobs is shaped by role scope, technical depth, domain experience, geography, and the size and compensation philosophy of the employer.
The same degree can therefore lead to different salary outcomes for different graduates. A research-oriented graduate entering an academic lab may see a different salary path than a graduate entering a product-focused engineering team at a large technology company.
- 1.
Skills
Having skills in subdisciplines like machine learning, robotics, and computer vision or with software like Python, Java, R, Apache Spark, or Amazon Web Services can increase your competitiveness and salary potential from AI jobs. Familiarity with tools such as Apache Spark, TensorFlow, and PyTorch can also be useful in technical roles.
- 2.
Experience
AI specialists with more professional experience and seniority tend to attract more money in salaries than those just starting in the field. Internships, applied projects, research assistantships, and production engineering experience can all help demonstrate readiness.
- 3.
Location
AI specialists working in locations like New York, Washington, DC, San Jose, Seattle, and San Francisco often earn higher salaries due to higher cost of living and greater demand. Remote work can complicate this picture because some employers adjust compensation by location while others use broader national bands.
- 4.
Specializations and additional certifications
Some industries, such as finance and government, require additional skills, subject matter expertise, or security clearances. Those with these extras may receive higher salaries in return. Specializations such as computer vision, natural language processing, deep learning, cloud architecture, and MLOps can also affect role fit.
- 5.
Employer
Big tech companies competing for top artificial intelligence specialists may offer higher salaries and attractive benefits for people with in-demand AI skills. Top employers can include Google, Microsoft, Meta, and other technology, consulting, finance, healthcare, and government organizations.
What’s a Master’s in Artificial Intelligence?
A master’s in artificial intelligence is an advanced degree, usually offered by a computer science department, that’s intended to familiarize students with the landscape of artificial intelligence as well as give students the skills and other practical knowledge they need to undertake doctoral research or build and deploy artificial intelligence solutions in industry.
Core skills often include mathematics, especially statistics and linear algebra; programming using languages like Python, R, and Java; data pipeline skills such as data mining, data analytics, and data visualization; and the ability to write artificial intelligence algorithms and build artificial intelligence models using software like Apache Spark, TensorFlow, and PyTorch.
Potential knowledge areas include machine learning, including deep learning and neural networks; natural language processing; computer vision; and robotics. Most reputable AI master’s programs cover some combination of these areas, but programs can differ significantly in emphasis, project structure, thesis options, and industry connections.
At Northeastern’s Khoury College of Computer Sciences, for example, graduate students in the MS in artificial intelligence program first develop a comprehensive knowledge of artificial intelligence before choosing a specialization in robotics, machine learning, computer vision, intelligent interaction, or knowledge management. At Boston University, master's students have the opportunity to pursue independent projects, such as an MS thesis that they publicly defend in their final semester.
Northwestern University’s McCormick School of Engineering takes an interesting approach by offering dual tracks, one for those who plan to continue in artificial intelligence and one for those with advanced degrees who plan to take what they learn and return to their home discipline. In the former, MSAI, students complete an internship with one of Northwestern’s industry partners or work on a project in Northwestern’s artificial intelligence laboratory before finishing with a capstone project. In the latter, MSAI+X, students start with a programming and math bootcamp while foregoing some later components.
Who’s a Master’s in Artificial Intelligence For?
Northwestern’s bootcamp requirement for students without a computer science or math background is instructive. In general, applicants to artificial intelligence master’s programs are expected to have earned bachelor’s degrees in computer science, mathematics, or another technical field.
Though they don’t have a parallel track for students without a CS background, Northeastern similarly requires that incoming students have a strong background in computer science and mathematics. This background can be demonstrated by passing placement exams on the fundamentals of computer science and statistics, probability, and linear algebra, respectively, or acquired before beginning study through the completion of introductory courses.
Philadelphia’s Drexel University follows suit, requiring that students enter its Master’s in AI and Machine Learning program with a four-year bachelor’s degree or master’s degree in computer science, software engineering, or a related STEM field with relevant work experience.
That does not mean every student must have the exact same path. Some programs are designed for working software engineers, some for research-oriented students, and some for professionals who want to apply AI within a specific domain. If you are comparing programs, look closely at prerequisites, bridge coursework, placement exams, portfolio expectations, capstone requirements, and support for internships or employer networking.
What Kinds of Careers Are Open to AI Master’s Graduates?
We’ve already covered how much artificial intelligence engineers, research scientists, data scientists, and machine learning engineers can make — but what exactly do they do with their master’s educations?
The following role snapshots preserve the original examples while framing them as illustrative career paths. Actual job descriptions, salary ranges, and degree expectations can change by employer and market conditions.
Artificial Intelligence Engineer
Artificial intelligence engineers focus on developing artificial intelligence models that can be deployed in real-world contexts — though the professionals with these responsibilities often have job titles like software engineer, AI specialist, and machine learning engineer. There are also more specialized AI engineer positions like robotics engineer, big data engineer, and business intelligence developer.
At Covera Health, an entry-level AI engineer working in computer vision and health imaging had the opportunity to leverage AI solutions to ensure accurate diagnosis within radiology, helping people access quality care regardless of location. Key responsibilities included consulting on Amazon Web Services platform optimization, designing and shipping AI models, and communicating results to internal and external stakeholders.
Requirements included a bachelor’s or master’s degree in computer science or a nearby field, one to three years of experience as a software or AI engineer, experience with SQL and a programming language like Python or C++, Unix environments, machine learning models, deep learning pipelines, and ideally deep learning inference engines like TritonRT. On Glassdoor, an AI Engineer at Covera Health — a small health services company — was listed at $137,022 annually.
Data Scientist
Data science isn’t normally considered a subdiscipline of artificial intelligence, but rather a discipline unto itself, albeit with some overlap. Regardless, the data scientist is frequently included among top artificial intelligence careers.
In terms of responsibilities, a data scientist ideates and executes novel approaches that turn raw data into business insights and solutions. After understanding business needs, data scientists determine what types of data are relevant and what questions need to be asked, then help develop machine learning models and predictive analytics to efficiently carry out the analysis. After the analysis, a data scientist is usually responsible for communicating results to relevant stakeholders.
A principal data scientist role at Mars, the candy and pet food conglomerate, illustrates the senior end of this career path. Mars looked for previous experience using data science or data analytics to drive business change, diverse technical experience with statistical analysis, fluency with Python and PySpark, previous experience in consumer packaged goods, retail, or healthcare, and leadership, mentorship, communication, and critical thinking skills.
At Mars, a qualified candidate would take the lead on data science projects in the pet food division, oversee junior data scientists, implement machine learning techniques and models, employ data visualizations to communicate findings, and maintain focus on business goals across projects. A candidate with a master’s degree hired for this position could expect to make at least $125,000 annually with benefits.
Research Scientist
While there is considerable overlap between data scientists and research scientists — both require backgrounds in mathematics, programming, and data management — they differ in their research. While data scientists are often focused on business intelligence that can be immediately applied, research scientists often work on more theoretical problems with less immediately applicable solutions.
An assistant research scientist working in computer disease simulation modeling at New York University’s Grossman School of Medicine offers a good example. NYU expected a qualified candidate to have at least a master’s degree in a relevant discipline, ideally computer science, applied mathematics, or data science, with some real-life experience.
The role also called for fluency with Python, R, C, or C++; experience programming Markov modeling; experience undertaking medical literature reviews; a background in advanced statistics and epidemiology; and proficient communication skills. Responsibilities included generating research ideas, managing projects, developing research techniques, assisting in data gathering and interpretation, preparing findings for publication, and maintaining current subject matter knowledge in epidemiology and biostatistics.
There is wide variation in research scientist salaries depending on the particular industry or discipline, but PayScale puts the average salary at $134,456 annually. Given that the NYU position is a more junior role in academic medical research that still requires a master’s degree, the starting salary would likely be lower than this average.
Machine Learning Engineer
A machine learning engineer is responsible for designing, developing, and shipping machine learning models — and then maintaining them once they are shipped and deployed to a live product. An ML engineer might work on a team focused on a particular product or feature, or they might work as a generalist and move between project types.
Machine learning engineers can also be responsible for managing data systems and undertaking data analysis, such as analyzing data sets from A/B tests on a machine learning system or algorithm. ML engineers are tasked with using machine learning skills to solve real-world problems, so their efforts can have a measurable effect on the lives of real people.
A machine learning engineer role at Glassdoor in Chicago, focused on powering the search experience, called for a B.S. or above in computer science or a related field; at least two years of experience applying machine learning best practices and deploying machine learning models; hands-on experience using structured and unstructured data; experience in natural language processing; ownership of medium- and large-size products; real-world experience with supervised and unsupervised learning; big data experience; and strong written and verbal communication.
At Glassdoor, a successful candidate would collaborate with an engineering team, use cloud-based software tools to enhance data pipelines and improve ML model training and testing, develop algorithms to determine quality of user-submitted reviews and salaries, and work across teams while overseeing projects end to end. The listed salary range was $129,300–$193,900 annually, with candidates holding a master’s degree potentially entering toward the higher end of the range.
Next Steps
If you’re attracted by the salaries offered to those with master’s degrees in artificial intelligence and are keen to learn more, start by clarifying the role you want, the technical gaps you need to close, and whether graduate school is the best way to close them.
If you’re looking to learn more about what a master’s in artificial intelligence entails, read AIFwD’s deep dive on the degree. If you’re ready to compare online options, start with our guide to online master’s in artificial intelligence.
If you want to learn more about how artificial intelligence is making a difference in key industries, you can also read about the role of machine learning in business and machine learning in medicine. Increasingly, the world will need bright minds working on artificial intelligence problems — and salary research is one practical part of planning that path.
Frequently Asked Questions
How much can you make with a master’s in artificial intelligence?+
PayScale reports an average salary of $102,848 for someone with a Master of Science in Artificial Intelligence, but actual pay varies by role, skills, experience, location, employer, and specialization.
Which AI master’s jobs tend to pay well?+
Common high-paying paths include artificial intelligence engineer, research scientist, senior data scientist, and machine learning engineer. These roles can overlap, and titles vary by employer.
Does a master’s in artificial intelligence guarantee a higher salary?+
No degree guarantees a specific salary. A master’s can help demonstrate advanced preparation, but compensation also depends on portfolio strength, production experience, technical specialization, market demand, location, and employer type.
What should I compare before enrolling in an AI master’s program?+
Compare prerequisites, curriculum, faculty expertise, thesis or capstone options, internship access, career outcomes, total cost, modality, and how well the program aligns with roles such as AI engineer or machine learning engineer.
Conclusion & Next Steps
A master’s in artificial intelligence can lead to high-paying technical and research roles, especially when paired with strong programming, machine learning, data, cloud, and domain skills.
The most useful salary research connects degree choice to role choice. Before enrolling, compare target jobs, salary ranges, program cost, prerequisites, and the kinds of projects or experience you need to compete in the market.
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