What’s the Average Machine Learning Engineer Salary?

As artificial intelligence (AI) finds increasing prevalence in our modern economy, machine learning engineering is rapidly gaining popularity.

Gone are the days when basic data management skills were sufficient. Today, we require machine learning engineers to design and develop complex algorithms that enable organizations to manage tasks ranging from predictive analytics to natural language processing, and much more. 

If you’re considering a career in this exciting field, you’re probably wondering about the earning potential. So, what’s the average machine learning engineer salary? 

In this article, we’ll dive into machine learning engineering, exploring what the role entails. We’ll also dip into the current job market and examine the average ML engineer salary based on location, industry, and experience. 

We’ll cover:

1. Machine learning engineer salary by location
2. Machine learning engineer salary by experience
3. Machine learning engineer salary by industry
4. What do machine learning engineers do?
5. Summary
6. Machine learning engineer FAQ

Ready to chart a path in this exciting and lucrative field? Let’s get into it.

1. Machine learning engineer salary by location

Hold on to your hats, because we’re about to find out the average salaries of machine learning engineers across the globe!

We’ve gathered insights from one of the industry’s leading sources—the renowned salary comparison website, Salary Expert. Their salary estimates are based on 30 years of real-world data from the Economic Research Institute and are available in local currencies.

Fear not, though, we’ve done the math for you and converted everything into U.S. dollars for easier comparison. Be sure to check out the links for the most up-to-date figures.

We’ve scoured the world for the top countries where machine learning engineers are in high demand:

1. Switzerland: $131,860 (or 123,704 CHF)
2. United States: $127,301
3. Australia: $103,005 (or AUD $155,778)
4. Germany: $101,216 (or €95,880)
5. Canada: $93,915 (or $129,633 CAD)
6. Singapore: $92,9790 (or $125,756 SGD)
7. United Kingdom: $83,633 (or £70,422)
8. France: $81,412 (or €77,113)
9. Japan: $78,693 (or 10,722,716 JPY)
10. Sweden: $66,439 (or 712,448 kr)
11. South Korea: $65,255 (or 86,183,911 krw)

Switzerland, the United States, and Australia are leading the pack with some of the most competitive salaries for machine learning engineers. Generally speaking, Europe and North America offer some of the best pay packages in the industry, which is unsurprising as they are home to some of the world’s largest economies. That said, countries across Asia are leading the way here, too.

Be mindful that salaries will vary not just between countries but regionally, as well. For example, if you’re keen to work in the tech hub of San Francisco, you can expect a salary of around $172,678. But, if you’re eyeing up a similar gig in a smaller city like Austin, Texas, you may have to settle for an average machine learning engineer salary of $133,251. Neither salary is too bad though, so don’t be too disheartened!

2. Machine learning engineer salary by experience

Another factor that will heavily impact your earning potential as a machine learning engineer is your experience level.

If you’re a talented developer with experience in IT management (for example), moving into machine learning could be a natural fit. Your experience is also likely to lead to a higher starting salary. Meanwhile, if you’re completely new to the field, you should expect to earn a bit less.

In this section, we’ll explore the average salaries of different levels of machine learning engineers. If you’re reading this post in the first place, you’re likely at the start of your career. But we’ll cover mid and late-career salaries, too, so you have something to aspire to! 

To keep comparisons consistent, we’ve stuck to figures from salary comparison website Payscale.

Entry-level machine learning engineer salaries

You don’t necessarily need work experience as a machine learning engineer to land an entry-level role. In fact, some employers are keen to train new starts using their proprietary systems and processes.

That said, you’ll still need to prove your knowledge, perhaps with an online course certificate or, better yet, a higher-level qualification in an area such as software engineering or artificial intelligence systems.

According to Payscale, entry-level machine learning engineers in the U.S. earn an average of $96,000 annually, or anywhere between $70,000 and $132,000. Even the lower end of this scale is significantly above the U.S. real median personal income.

Skills for entry-level machine learning engineers

At this stage, you’ll be learning data science basics, including:

• data modeling
• image processing
• big data analytics
• machine learning tools

You should also be perfecting your programming expertise using a versatile machine learning language like Python.

In general, you should have a strong foundation in math (especially statistics) and familiarity with popular machine learning algorithms and libraries, like scikit-learn and TensorFlow.

You’ll also be able to demonstrate more fundamental data analytics skills, including the ability to clean and preprocess data and visualize insights.

Mid-career machine learning engineer salaries

Payscale suggests that mid-career machine learning engineers in the U.S. (those with about 5-10 years of experience) can earn an average of $144,000, and anywhere between $99,000 to $180,000.

Skills for mid-career machine learning engineers

At this stage, you should have quite a few skills under your belt. Here are a few of them:

• A deep understanding of machine learning techniques such as neural networks and deep learning
• Advanced expertise in at least one machine learning framework like PyTorch or Keras
• Familiarity with distributed computing and cloud platforms like Azure
• Having an additional programming language or two under your belt, such as C++ or JavaScript

Finally, in addition to the above you should specialize your focus on a particular domain area based on your interests and strengths.

Late-career machine learning engineer salaries

Lastly, Payscale suggests that late-career machine learning engineers in the U.S. (approximately 10+ years of experience) can earn an average of about $150,000. However, the real figure could be anywhere between around $115,000 to $204,000.

Skills for late-career machine learning engineers

By this stage, you’ll be specializing in an area such as natural language processing or computer vision. On top of that, you’ll have:

• Broad knowledge of other AI techniques
• Designing highly scalable systems
• Proficiency in multiple programming languages
• Familiar with regulatory and compliance requirements

In fact, you’ll likely be shaping these skills in a leadership role. If that’s the case, your earning potential could be even higher, especially once taking into account additional perks like bonuses and healthcare benefits.

3. Machine learning engineer salary by industry

Finally, the industry you work in can also affect your salary.

In this section, we’ve got you covered with a quick overview of the top-paying industries for this role in the U.S. And if you thought machine learning was only important for big tech, you might be surprised by the results!

According to data from Glassdoor, the top 5 paying industries for machine learning engineers in the United States are:

• Real estate
• Information technology (Okay, we’ll let you have that one–it’s tech!)
• Retail and wholesale
• Healthcare
• Human resources

Real estate takes the crown as the top-paying industry, with a median total salary for machine learning engineers of $194,101 per year.

Information technology comes in a close second, with a median total pay of $185,687 per year. 

Retail and wholesale follows closely behind, with a median total pay of $160,985 per year.

Healthcare and human resources round out the top five industries, with median total salaries of $159,740 and $150,057, respectively.

Of course, keep in mind that while these industries offer high salaries, your specific pay will depend much more on factors like location, experience level, and job responsibilities.

By researching industry trends and demand for machine learning engineers in different sectors, you’ll get an even better idea of what to expect. 

But the best way of all? Start applying for jobs! 

4. What do machine learning engineers do?

Okay, so now we’ve looked at how much you can earn, let’s ask a more fundamental question: what exactly do machine learning engineers do?

Machine learning professionals are responsible for designing and developing algorithms that allow machines to learn from data and make smart decisions.

The role of an ML engineer typically involves working with massive amounts of data. They will identify patterns, build models, and deploy these algorithms. They’ll also be responsible for maintaining these systems, ensuring they deliver accurate, relevant results over time.

As a machine learning engineer, you could be responsible for anything from data preprocessing to model selection and evaluation, feature engineering, and deployment. You’ll likely work with technologies like Python, machine learning libraries like TensorFlow, and distributed computing systems such as Hadoop.  

Related reading: PyTorch vs TensorFlow

And, of course, you’ll have to collaborate closely with other professionals in the field. This means data scientists, software developers, and business analysts, to name a few.

If you’re interested in using your skills to build intelligent machines that can tackle complex problems, a career as a machine learning engineer could be ideal for you. 

5. Summary

So there we have it! In this article, we’ve explored the whole realm of ML, highlighting some profitable machine learning engineer salaries for those possessing the right skills and expertise.

Notably, the average machine learning engineer salary varies depending on geographical location, industry, and experience level, with Switzerland, the U.S., and Australia offering some of the highest salaries globally.

In terms of experience, in the U.S., entry-level salaries hover around $96,000, mid-career salaries around $144,000, and late-career salaries can be upwards of $150,000 per year. While these are just estimates, they clearly indicate fast early career growth that can result in a promising income even before you reach the higher echelons of expertise.

Finally, we examined the industries in the U.S. with the highest-paying machine learning jobs. While the tech industry is unsurprisingly close to the top of the list, unexpected entries include:

• real estate
• retail and wholesale
• healthcare
• human resources

All this is evidence that machine learning is no longer the preserve of companies focused on building technologies, but that all businesses are increasingly technology-driven.

CareerFoundry’s Machine Learning with Python course is designed to ease you into this exciting area of data analytics. Possible as a standalone course as well as a specialization within our full Data Analytics Program, you’ll learn and apply machine learning skills and develop the experience needed to stand out from the crowd.

You can read more about the fascinating and fast-evolving field of machine learning in the following introductory guides:

• 22 Most-Asked Machine Learning Interview Questions (and Answers!)
• 4 Levels of Measurement: Nominal, Ordinal, Interval & Ratio
• The Best Data Science Bootcamps in 2024

6. Machine learning engineer FAQ?

Are ML engineers in demand?

Machine learning is a rapidly growing field with high demand for skilled professionals. Machine learning engineers are in high demand across a variety of industries, including healthcare, finance, retail, and manufacturing. A quick search on job site Indeed for the position in the United States in December 2023 brings up over 16,000 job openings

Is machine learning difficult?

Machine learning is a challenging field that requires a strong foundation in mathematics, computer science, and data. However as we’ve explored here, it’s also a rewarding field with a high potential for career growth.

What are the most popular machine learning frameworks?

TensorFlow, PyTorch, scikit-learn, Apache MXNet, and Keras are some of the most popular machine learning frameworks.

What are the top machine learning companies to work for?

Some of the best machine learning companies for ML engineers to work in are tech giants, such as Google, Amazon, Microsoft, Salesforce, and IBM.

What are the best certifications for machine learning engineers?

A whole ton of machine learning courses and certifications have emerged in the last year. It’s import to choose an ML certification course from a recognized provider that is suited to your own learning style and goals. CareerFoundry launched a Machine Learning with Python course which includes with their successful dual mentorship learning model, where you’ll learn the basics of machine learning with the support of a tutor and mentor.