Machine Learning (ML) has dramatically reshaped industries, leading to the emergence of new trends and technologies. From the intersection of ML and IoT, automated machine learning, machine learning in cybersecurity, and the rise of AI ethics, or AI engineering, the role of a machine learning engineer has gained significance. This also boosts the demand for skilled professionals.
Consequently, the compensation packages offered to ML engineers are also some of the best. In this salary guide, we will break down the factors that determine a machine learning engineer’s salary. We will also look at how you can build a high-paying career in this field by leveraging AI ML programs.
Who is a Machine Learning Engineer?
Machine learning has gained the world’s attention thanks to its ability to bring meaningful insights from vast volumes of data. It is a branch of AI or artificial intelligence that enables computers to learn from data and make predictions. It can also make programs from this learned data without being explicitly programmed.
A machine learning engineer applies ML techniques to problems and domains and creates solutions. These domains include natural language processing, computer vision, recommender systems, self-driving cars, etc. They use these techniques to transform data science models into scalable and robust solutions deployed to production environments.
Also Read: What is Artificial Intelligence? A Beginner’s Guide
What Do Machine Learning Engineers Do?
ML engineering is a relatively new area of expertise, and it is still hard to define what ML engineers do. Depending upon the organization and the nature of the work, a machine learning engineer’s job often crosses paths with areas like data science and software engineering.
However, their role is often distinct from that of a data scientist. They are similar in that they both handle large datasets, but the objectives are different. Here are some of the responsibilities of a machine learning engineer.
Collaboration with Data Scientists
MLEs and data scientists often work together. Data Scientists focus on gaining actionable insights from vast data sets. They then relay their findings to business stakeholders. In contrast, MLEs ensure that the models created by Data Scientists are scalable and can process vast amounts of real-time data to get the results.
Designing Data Pipelines
Another major task they have is to create robust data pipelines. These pipelines facilitate the smooth flow of data. They ensure it’s cleansed, transformed, and ready for model ingestion.
Algorithm and Architecture Development
A core duty of MLEs is to devise algorithms that help with data processing and insight extraction. Additionally, they design software architectures that can handle machine learning processes.
Integration with Software Systems
MLEs work hand-in-hand with software engineers. This way, machine learning models are integrated into broader software systems. It makes them accessible and functional for end-users.
In essence, machine learning engineers serve as the bridge, linking the theoretical and practical aspects of data. Machine learning engineers cover the distance from data science to software implementation.
How Much Do Machine Learning Engineers Earn?
There is a surging demand for machine learning engineers. This stems from the increasing complexity of machine learning, the growing availability of machine learning tools in business, and a push for automation. It has led to a shortage of skilled professionals in the field and a proportional increase in value for the role.
Machine learning engineers (MLEs) command impressive salaries in today’s job market. Entry-level MLEs can expect to start with an average salary of around $108,473 per year. This rises with experience and expertise and can be around a yearly average of $160,407 with 10-14 years of experience.
The most prominent players like Google, Meta, and Pinterest are known to offer the highest salaries for these roles globally.
With such a lucrative pay scale and a key role in innovation for the future, the prospects of being a machine learning engineer are bright. You can get started on this learning curve by investing in valuable programs like our AI ML bootcamp.
As the times change, so are the salaries. Let us look at some of the factors that determine the salary of a machine learning engineer.
Machine Learning Engineer Salary
Machine learning engineer salaries vary from place to experience and various other factors. In this section, let’s break down these factors to give you a better idea of what to expect in this profession.
Experience
As with many professions, experience plays a role in determining a machine learning engineer salary. Beginners can get an entry-level salary of around $85K – $139K/yr. But as you learn and grow, your salary scale will change too. A mid-level engineer with around 4-6 years of experience can expect a salary of around $105K – $168K/yr in the US. In contrast, a seasoned professional with over 15 years of experience will get a senior machine learning engineer salary of around $137K – $224K/yr.
Location
The geographical location significantly impacts the salary scales. Some countries have thriving tech ecosystems, while others have a higher cost of living. Some metropolitan hubs have a concentration of tech companies, while others don’t. Depending upon which place you choose to work in, your salary can vary.
Here are some top-paying locations:
New York: $101K – $167K/yr
San Francisco: $117K – $187K/yr
Boston: $99K – $154K/yr
San Jose: $109K – $173K/yr
Company
Your pay can also change from one company to another. The stature and financial health of a company can influence the pay packages it offers. Tech giants like Google or Amazon are known for their generous compensation packages.
Here are some top companies to set eyes on when looking for a job: (source)
Meta $271,723
Google $246,428
Pinterest $241,118
Twitter $238,867
Cruise $231,603
Netflix $227,163
Apple $224,960
Snap $223,731
eBay $222,877
Amazon Web Services $222,248
Industries
The employment industry also dictates a machine learning engineer salary. Sectors like finance, e-commerce, and healthcare have a lot of applications of machine learning. They heavily rely on data-driven insights. Hence, such industries are likely to offer better compensation.
Here is a look at:
Financial Services $104K – $168K/yr
Pharmaceutical and Biotechnology $97K – $158K/yr
Personal Consumer Services $99K – $162K/yr
Information Technology $101K – $159K/yr
Retail and Wholesale $97K – $158K/yr
Skill Set
Beyond generic machine learning expertise, possessing specialized skills or proficiency in specific tools can increase your chances of getting a higher machine learning developer salary. Professionals proficient in deep learning, natural language processing, or popular frameworks like TensorFlow can command higher salaries. Due to the niche nature of these skills, there could be a higher demand for such professionals.
Here is the salary scale for different machine learning specialist roles in the US;
Conversational AI Engineer $200,000/yr
Machine Learning Engineer $95,000/yr
Machine Learning Researcher $100,000/yr
In short, machine learning is a field that has an enormous scope and equally large packages. Candidates willing to stay ahead of the curve by acquiring new skills and staying relevant can find themselves in a good position.
Also Read: What is Machine Learning? A Beginner’s Guide
How Machine Learning Courses and Certification Can Impact Salary
Because this is an innovative field, you’ll always encounter something new. Continuous learning is a key aspect of an ML career. Therefore, investing in AI ML training and courses aren’t just an option; they are a necessity if you wish to thrive in this career. Here is our expert take on why it is a great way to kickstart or transition your career in ML engineering.
Enhancing Skills and Knowledge
It never hurts to learn the latest skills and knowledge in the field. It can be detrimental in deciding whether you break into the role. Choose a program that offers theoretical and practical knowledge in data analysis, programming, algorithms, statistics, and more. Your chances of getting hired, promoted, and paid more are higher with such a certification.
Increasing Demand and Value
There is no doubt that machine learning is one of the most in-demand and valuable skills in the current job market. With many applications in various industries, it is becoming a skill that every industry is looking for. Getting a certificate can increase your value in the job market.
Boosting Salary and Income
Relevant courses and certifications can help professionals boost their machine learning engineer salary. As machine learning is one of the highest-paying fields, you can get a valuable certification through an online AI ML program and earn a bigger paycheck.
Therefore, machine learning courses and certification can have a positive impact on your salary.
Become a Highly-Paid ML Engineer With the Right Course!
The world of technology is rapidly evolving, and you must do what it takes to position yourself in the forefront. As the article covered, it comes with very high compensation, making it a competitive area.
However, what can set you apart from the competition is your skills and credentials. And what better way to raise your credentials than with a prestigious certificate? Here is a quick look at what our AI ML bootcamp offers.
The AI and Machine Learning Bootcamp is a unique learning experience that combines academic excellence with hands-on expertise from global AI leaders. You can dive deep into cutting-edge AI topics, from generative AI to prompt engineering. There are also over 25 real-world projects and live sessions. The curriculum is designed for immediate career impact and comes with a certificate of completion that adds significant professional value.
Ready to elevate your career and your machine learning engineer salary with in-demand AI and ML skills? Enroll today
