The 5 Highest-Paying Machine Learning Jobs in 2025

Over the past few years, the explosive growth of the artificial intelligence (AI) field has been nothing short of revolutionary. From ChatGPT and digital voice assistants to transformational advances in health care and finance, AI is becoming a bigger part of everyday life than ever before.

A branch of data science called machine learning (ML) is largely responsible for the launch of the current AI revolution. In simple terms, machine learning models are digital frameworks that allow machines to recognize patterns, make decisions, and learn in a way similar to humans.

The global AI industry is expected to grow twentyfold between 2021 and 2030, and with it, so will the demand for skilled machine learning professionals. If you’re interested in an exciting career path that you can pursue from anywhere, join us for a look at five of the highest-paying jobs in machine learning. We’ll also explain how to break into the field, what to expect as you progress, and more.

1. Machine learning engineer

Machine learning engineers are skilled data scientists who build the frameworks that allow artificial intelligence to develop without additional programming. Through software development, machine-learning algorithms, and fluency in Python and Java, these professionals give machines the datasets they need to function independently.

On a typical day, you might find an independant machine learning engineer developing a new app for a client, creating a predictive algorithm, or making a piece of existing software more efficient. ML engineers combine creativity with a thorough understanding of statistics and software engineering to put the “smart” in smart technology.

While pay may vary based on client and experience level, Upwork is home to a wide variety of skilled freelance ML engineers who regularly bring in $25 to $50 per hour, depending on the project and specialty.

2. Data scientist

Data science has made it possible for businesses to collect massive amounts of information online. But all that data doesn’t mean much unless an organization can figure out how to turn it into useful insights. That’s where data scientists come in.

Professionals working in data science use their problem-solving skills and mastery of platforms like TensorFlow to build machine-learning algorithms capable of extracting useful information. Google Analytics, for example, is a tool that allows website owners to transform website traffic data into actionable business insights.

Like machine learning engineers, data scientists can expect to earn an hourly rate of $25 to $50 per hour. According to the Bureau of Labor Statistics (BLS), demand for data scientist roles is projected to grow an incredibly healthy 35% from 2022 to 2023.

3. AI engineer

Artificial intelligence engineers specialize in equipping machines with the human-like skills needed to complete complicated tasks. Many AI engineers enjoy an exciting range of projects, from developing machine learning algorithms and neural networks to data mining and software engineering.

By combining AI, deep learning, and robotics, AI specialists can solve problems that are difficult to tackle with traditional machine learning techniques alone. Skilled AI engineers are in very high demand and enjoy hourly rates of $35 to $60.

Major companies like Google and Apple may pay much more for the right experience level. If you’re looking for a career path that offers plenty of demand no matter where you live, AI engineering is a great choice.

4. Computer vision engineer

While a machine learning engineer teaches a computer to learn, a computer vision engineer teaches it to process and make sense of images. Computer vision is a fascinating field with plenty of real-world applications, including facial recognition security and self-driving vehicles.

Computer vision engineers come in a variety of different specialties, which is what makes Upwork such a great place to connect with clients searching for your unique skill set. Most computer vision professionals are fluent in a common programming language such as Java or Python and are comfortable working with deep learning tools like TensorFlow or PyTorch.

Hourly rates for these professionals span a wide range on Upwork, but an entry-level computer vision engineer can expect to bring in an annual salary averaging just over $100,000.

5. Natural language processing scientist

Natural language processing (NLP) engineers combine computer science and linguistics to help machines process and use human language. The tools of their trade include platforms like the Python-based Natural Language Toolkit (NLTK) and statistical NLP, a blend of deep learning and machine learning models.

NLP professionals make it possible for people to communicate with voice assistants like Siri and Alexa, interact with chatbots, and use tools like Google Translate. While some of these skilled scientists specialize in NLP, others also offer services in computer vision, engineering, and data science.

The hourly rates vary widely for NLP freelancers on Upwork, but NLP roles bring in an average salary of just over $116,000 per year. That said, average hourly rates can vary widely based on each professional’s experience level or the scope of an individual project.

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Breaking into the field of machine learning

Demand for top machine learning and artificial intelligence talent is higher than ever before, and there’s no sign of it slowing down any time soon.

What will you need to break into one of today’s fastest-growing industries? Let’s take a closer look at what it takes to become an ML expert.

Skills and specializations needed

Working with top machine-learning clients can be incredibly lucrative, but you’ll need to master several vital skills first. In order to work with machines, you’ll need a solid understanding of the programming languages and algorithms that make them tick.

In your quest for technical knowledge, don’t forget the importance of soft skills, which can set you apart from the competition. Whether you’re just getting started or are well on your way to becoming an expert, here are some of the most in-demand skills in machine learning.

• Foundational knowledge. Machine learning requires a thorough understanding of computer science, as well as several mathematical fields like linear algebra, probability, calculus, and statistics. If you’re still in school or are just getting started, make sure you gain a comprehensive knowledge of these areas.
• Programming proficiency. You’ll also want to become fluent in programming languages like Python, R, C++, and Java. Python tends to be particularly essential for machine learning talent, so it’s a great place to start.
• Algorithms. Machine learning algorithms, from basic regression models to advanced neural networks, are also important components of the ML expert’s toolkit. You’ll want to get very comfortable working with deep-learning frameworks and algorithm libraries like SciPy, Numpy, and Matplotlib.
• Soft skills. Top clients love working with talent who are skilled in problem-solving, critical thinking, and effective communication. These traits will ensure you’re able to translate technical insights into actionable business strategies.

Educational requirements

Machine learning offers a wide variety of learning paths, from university degrees to online certifications and boot camps. Here are several ways to gain the skills you’ll need as an ML expert.

• Self-learning. Online learning platforms like Coursera, Udemy, and edX offer excellent opportunities to master essential machine-learning skills at your own pace. You can also earn top Python certifications with the help of OpenEDG’s Python Institute courses.
• Bootcamps. Online tech boot camps like the ones you’ll find at General Assembly offer intensive training and hands-on experience. Springboard also provides an impressive selection of AI and data science courses, some of which even come with a job guarantee.
• Formal education. Many machine learning professionals start out by earning a bachelor's or advanced degree in computer science, data science, or mathematics. While some clients prefer to work with professionals who hold degrees in a certain field, others are more concerned about finding talent with the skills needed for their projects.

Machine learning career progression

Much like any other career path, the machine learning field is made up of professionals of all different experience levels. Here’s a look at the type of opportunities you’ll likely encounter at different stages of your career.

Entry-level roles

Some of the highest-paying machine learning work isn’t exactly entry-level. The good news is that you’ll find plenty of opportunities that can help you build a portfolio over time. When you’re first starting out, consider job titles like these, which can offer an entry point into the field of machine learning:

• Software engineer
• Data analyst
• Junior machine learning engineer
• Research assistant
• Associate data scientist

Mid-level roles

As you gain experience and skills, you’ll be able to start working your way up the ranks. The machine learning field is continually evolving, so the more skills you obtain, the more demand you’ll enjoy. Once you establish a solid track record, you’ll be ready to look for work as one of the following:

• Machine learning engineer
• Data scientist
• NLP scientist
• Business intelligence (BI) developer
• AI engineer

Senior and leadership roles

Becoming a highly skilled machine learning professional isn’t easy, but it’s a sure way to enjoy access to some of the highest-paying work in the industry. Here are examples of top-level machine learning roles you may want to aim for depending on your interests and specialties:

• AI architect
• Lead data scientist
• Chief data officer
• Senior machine learning engineer
• President or VP of artificial intelligence and machine learning

Charting the most lucrative machine learning career path

Machine learning engineer salaries and hourly rates depend on a number of factors, such as your years of experience and skill set and a client’s location. Let’s explore several factors you’ll want to consider when determining your ideal rate.

Where do ML engineers make the most?

It may come as no surprise that you can expect to find some of the highest ML salary ranges in or around major U.S. tech hubs. According to Indeed, ML experts in Santa Clara, CA, (Silicon Valley) earn some of the highest salaries in the nation averaging around $180,000, or around $125,000 on the low end to over $270,000 a year.

New York City offers an even wider salary range, with lows just over $100,000 and highs of more than $300,000. Companies in Seattle also pay very generously, with average annual salaries of nearly $170,000 that reach over $250,000 for the highest earners.

Seeking remote clients from these areas may grant you access to higher-paying work without paying for a higher cost of living. Upwork’s 2022 Future Workforce Report revealed that 60% of all hiring managers cite difficulties finding quality talent, with data science and analytics roles being the hardest positions to fill.

Due to the recent surge of remote and contract work opportunities, now is an excellent time for ML experts to enter a high-demand field from anywhere.

Which companies pay the most for ML jobs?

Amazon, Google, and major social media companies like Meta offer some of the highest salaries for machine learning engineers, but startups are also an excellent place to forge long-lasting working relationships by getting in on the ground floor.

You can also find contract work with top AI companies all over the world. Some of Upwork’s top-rated clients include companies from countries such as India, the United Kingdom, Spain, and the United Arab Emirates.

Ways to boost your ML earnings

Achieving consistent job success in the machine learning field often depends on staying aware of the latest trends in an ever-evolving industry. Continuous learning and certification courses are always great ways to increase your skills–and rates–over time.

Here’s a collection of top certifications and courses that can help take your career to the next level:

• IBM’s Machine Learning Professional Certificate
• Amazon’s AWS Certified Machine Learning Specialty Certification
• Google’s Professional Machine Learning Engineer Certification
• Microsoft’s Azure Data Scientist Associate Certification
• Cornell’s Machine Learning Certificate Program
• Harvard’s Professional Data Science Professional Certificate
• Stanford’s Machine Learning Specialization

The road ahead for machine learning professionals

In this era of rapid technological innovation, machine learning is emerging as one of today’s highest-paying career paths. Whether you’re ready to start building your professional portfolio or setting your own hours in an ML role, investigate the many machine learning jobs you’ll find on Upwork.
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Upwork does not control, operate, or sponsor the tools or services discussed in this article, which are only provided as potential options. Each reader and company should take the time to adequately analyze and determine the tools or services that would best fit their specific needs and situation.