According to the PWC Global AI reports, artificial intelligence might spend around $15.7 trillion by 2030 for the global economy, more than China and India’s total GDP now. AI is being used by businesses to increase efficiency and revenues.
Artificial intelligence (AI) engineers contribute to rethinking how we employ machine learning (ML) algorithms, models, and tools to power our products, services, and global systems. They can easily earn a six-figure AI ML engineer salary because this sort of work necessitates a high level of technological competence.
AI and machine learning experts are in great demand in many businesses worldwide, whether working on computer vision using deep learning or developing algorithms to generate real-time market forecasts in milliseconds.
But how can you seize these opportunities? This article will tell you everything about an AI ML engineer job, how much you can earn, and how to become one.
So, let’s get started!
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AI ML Engineer – What’s It All About?
The job of an AI ML engineer is critical and highly regarded for one simple reason: only some people are predisposed to be one, and their abilities are priceless.
So, what exactly is a machine learning engineer, and what exactly does he (or she) do? “machine learning engineer” & “data scientist” are often used invariably. There are minor variances when the line blurs.
To begin with, data science is a wide word. It contains programming but is mostly concerned with data in an analytical way. As a data scientist, you examine data and create findings for your company that help it better.
A data science team can involve an AI ML engineer or specialist. ML is concerned with creating models that may be utilized to improve a product, for example. Machine learning experts can design an image recognition system that distinguishes different sorts of rubbish based on images, estimate the need for energy, forecast future product sales based on previous data, or forecast the path of an epidemic.
Some well-known instances are traffic prediction and the development of novel medicines that can kill many antibiotic-resistant microorganisms.
To achieve this, the AI ML engineer must be an expert in programming, probability, and statistics and a master of mathematics and computers. These are challenging abilities that not everyone can learn and use. These are a few instances of an engineer’s accomplishments with machine learning and data.
It is a growth-oriented position that many companies prefer since it aids in corporate development.
How Much Does an AI ML Engineer Earn?
Let’s take a look at the typical AI ML engineer salary. According to Indeed.com, the average standard AI ML engineer salary in the United States is $160,486 annually as of November 2023. The lowest price range is $104,570, and the highest is $246,302. These statistics may change depending on the outcome.
Now that we have established a median baseline let’s split AI ML engineer salaries by several mitigating variables. We must now consider factors such as experience, industry, and location.
Depending on your education, level of experience, geography, and company, machine learning engineers have some of the highest-paying AI jobs in the world. According to popular employment sites such as PayScale and Glassdoor, machine learning engineers generally make between $76,000 and $154,000.
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Various factors contribute to the broad range of average earnings of a machine learning engineer. Before taking a deal, employers usually assess qualities like expertise, skill levels, appropriate educational standards, demographics & domain knowledge, as evidenced by involvement in real machine-learning projects. So, let’s start with experience and look at the responsibilities of each level.
How does the AI ML Engineer’s salary vary?
The most pressing question is, how much do AL ML engineers earn? There is no definitive answer. The income of an AI ML engineer is determined by several aspects, including the firm, job title, country, and even locality. The most significant factor, however, is experience.
So, how does the AI ML Engineer’s salary vary?
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With Experience
Your expertise and understanding of the data science field determine the numbers on your account. The more information you have, the more value you may contribute to the firm. And the more value you add, the more you get compensated.
According to the information gathered by the author, the remuneration is as follows:
Entry-level AI ML engineer: The average salary for an entry-level machine learning engineer (with 0-4 years of experience) is around $97,090. However, with possible incentives and profit-sharing, that figure may quickly increase to $130,000 or higher.
Mid-level AI engineer: The average compensation for a mid-level machine learning engineer (5-9 years of experien ce) is $112,095.With possible rewards and profit-sharing, it might be $160,000 or more.
Senior AI ML engineer – (10+ years of experience) – average income of $132,500; with incentives and profits, the figure can reach $181,000 annually.
Additionally, skilled machine learning engineers with 10 to 19 years of relevant expertise may earn an annual average income of $150,708. Ultimately, late-career specialists with 20 years or more receive an average annual total remuneration of $150,322.
💡You can check entry level and senior level ai jobs at AI Careers for free.
The more knowledge you have, the more your skills and time are valuable to potential employers. Remember this while applying for jobs and when it comes time for your yearly review and merit raise. Refrain from underselling yourself if you have the necessary AI ML abilities or expertise!
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By Industry
Unsurprisingly, when you explore the AI ML engineer salary situation in different industries, you will see that some pay more than others. Here is a summary of the top five machine learning engineers’ salaries, according to Glassdoor.com.
- Real Estate – $187,938. This rate is 13% greater than in other industries.
- Information Technology – $181,863. This rate is 10% greater than in other industries.
- Media and Communication – $161,520. This rate is 1% lower than in other industries.
- Retail and Wholesale – $157,766. This percentage is 3% lower than in other industries.
- Healthcare – $148,971. This percentage is 9% lower than in other industries.
Similarly, according to Indeed, the top 10 machine learning engineers’ salaries are based on the highest-paying organizations.
It’s hardly surprising that some of the most profitable corporations are also among the most well-known in the world. The top ten brands are Apple, Adobe, Facebook, LinkedIn, Twitter, Amazon, and Citizens.
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By Location
When making job offers to candidates, it is common practice to tie the AI ML engineer compensation to the location. There is a basic average median wage for machine learning roles, and employers adjust the offer depending on a cost of living index.
A machine learning engineer earns an average of $113,909 annually in the United States. However, you could be tricked if you only use a country as the criterion.
💡 Great news! We offer AI job opportunities in various locations, including the USA, India, Europe, Australia, and Canada.
The salary for machine learning might vary based on the job’s location. According to Indeed.com, the following cities in the United States have the highest ML wages.
How Can You Earn More as an AI ML Engineer?
Now that we’ve explored the AI ML engineer salary landscape, we should consider the career’s prospects. Is it worthwhile to get in? After all, while the money is excellent, the qualifications and standards are rigorous and necessitate substantial study and training.
The US Bureau of Labor Statistics projects that computer jobs will expand by around 13% during the next 10 years, ending in 2026. This projection is for IT roles in general, but we can assume from these data that machine learning will rise at the same rate.
Furthermore, NASDAQ believes that the artificial intelligence and machine learning sectors will be disruptive technologies, with a market value of $20 billion by 2025.
So, the ML engineer career path is promising!
But how do you earn more?
A successful engineer has three characteristics: quality, authority, and experience. Make sure you have these three. And to do so, you must continue to study, expand your talents, and be adaptable. There are multiple ways to elevate your knowledge:
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Participate in Conferences, Seminars, and Courses
Conferences can teach you much about the industry, the newest trends, and industry secrets. It’s also a terrific way to meet new people and specialists and possibly get a career.
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Learn New Skills
The best thing you can do is to use the information to your advantage. Several machine learning tools are available to help you learn new topics and broaden your present skill set.
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Move To A Different City
You can relocate to one of the places that will allow you to get better work, possibly in one of the greatest firms.
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Join communities
There are countless online forums and groups where individuals can learn, teach, meet new people, exchange ideas, and inspire one another to work more. Your neighborhood may have a local community. Join such a group and explore for ideas. Check out Kaggle, Stack Overflow, or Reddit.
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Start Networking
When attending conferences or being a part of a community, try to talk to as many individuals as possible. Having a network of trustworthy individuals can help you advance in your job. Reach out to people who motivate you to broaden your social network.
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Read books
There are numerous excellent publications available that may help you become a better machine learning engineer or even start from scratch.
Try anything, mix it up, and don’t give up.
Wrapping Up
Machine learning is required to automate specific jobs and procedures. Machine learning arose from pattern recognition and the idea that computers can learn without being programmed to do specific jobs. Artificial intelligence researchers wanted to see if computers could learn from data.
Machine learning engineers execute a range of machine learning experiments using programming languages such as Python, Scala, and Java, as well as the required machine learning libraries.
Some of the main talents required are programming, probability and statistics, data modeling, data structures, machine learning techniques, and system architecture. If you meet these prerequisites, you may be on your way to a very successful profession.
AI ML engineers could see a boom in the next few years as organizations strive to innovate and produce innovative goods. And one of the best ways for a firm to expand is to invest in technology and artificial intelligence.
