AI ML Engineer Salary: A Comprehensive Guide

As an AI ML Engineer, you're in high demand, and your salary reflects that. According to the US Bureau of Labor Statistics, the median annual salary for software developers, which includes AI ML Engineers, was $114,140 in May 2020.

The salary range for AI ML Engineers can vary greatly depending on factors such as location, industry, and level of experience. In the United States, for example, the average salary for an AI ML Engineer is around $141,000 per year, with top-end salaries reaching upwards of $250,000.

With experience, your salary can increase significantly. In the article section "AI ML Engineer Salary by Industry", we saw that AI ML Engineers in the finance industry tend to earn higher salaries, with an average of $173,000 per year. In contrast, those in the non-profit sector tend to earn lower salaries, with an average of $93,000 per year.

As a machine learning engineer, your salary is heavily influenced by your level of experience. Entry-level machine learning engineers can expect to earn around $96,000 per year, while mid-career professionals can earn upwards of $144,000 per year. Late-career professionals can earn even more, with some earning upwards of $150,000 per year.

To give you a better idea, here are some average salary ranges for machine learning engineers based on experience level:

Keep in mind that these are just averages, and your actual salary may vary depending on factors such as location, benefits, and specific job requirements.

As a mid-career professional, you're likely looking to take your skills and experience to the next level. In the United States, mid-career machine learning engineers can expect to earn an average of $144,000 per year, with salaries ranging from $99,000 to $180,000.

To achieve this level of earning potential, it's essential to develop a range of skills, including programming, data analysis, and domain specialization. Practical experience through actual problem-solving is also crucial for standing out and growing your salary.

Mid-career machine learning engineers in the U.S. can earn an average of $144,000, according to Payscale, which suggests that salaries can range from $99,000 to $180,000.

Here's a breakdown of what you can expect at the mid-career level:

These figures may vary depending on factors such as experience, location, and benefits. However, with the right combination of skills and experience, you can position yourself for significant salary growth and advancement in your career.

The salary of an AI/ML engineer can vary greatly depending on the industry they work in. In the United States, some of the top-paying industries for machine learning engineers include Information Technology, Human Resources & Staffing, Personal Consumer Services, Retail & Wholesale, and Energy, Mining & Utilities.

However, the IT, Healthcare, and Finance sectors stand out in terms of offering lucrative salaries and exciting opportunities. The IT industry is a top payer for machine learning engineers, with companies like Google and Facebook offering competitive salaries.

Machine learning engineers at Google and Facebook earn $147,992 and $122,619 per year on average, respectively. Other IT companies providing top salaries for Machine Learning Engineers include Dropbox, Cruise, and Synopsys.

In the Finance industry, machine learning engineers can expect an average salary of $128,317 per year. These professionals are predominantly employed in areas such as Banking, Financial Services, and Insurance (BFSI), where their expertise in data analysis and predictive modeling is highly valued.

Leading companies in the BFSI sector actively seek and competitively remunerate machine learning engineers to drive data-driven decisions and innovations. At the top of the market, machine learning engineers can earn as much as $171,278 annually in the IT industry.

Here is a list of the top-paying industries for machine learning engineers in the United States, along with their average salaries:

California is one of the top-paying states for machine learning engineers, with average salaries around $175,000 and top earners making upwards of $250,000 in tech hubs like Silicon Valley and San Francisco.

The San Francisco Bay Area, CA, is a specific location where machine learning engineers can earn a high salary, with an average of $158,303 according to Glassdoor.

New York is another state with high-paying machine learning engineer positions, with average salaries of approximately $165,000 and potential to earn higher in New York City’s competitive market.

In contrast, Austin, TX, has a lower average salary of $125,652, but it's still a growing tech scene worth considering.

Here's a breakdown of average salaries in some key tech hubs in the United States:

Machine learning engineers are among the highest-paid professionals in the technology sector, with many earning six-figure incomes. In fact, they can earn an average of $96,000 annually at entry-level in the U.S.

Their salaries can range from $70,000 to $132,000, with the lower end being notably above the U.S. real median personal income. This is likely due to the high demand and specialized skills required for the role.

Here's a comparison of machine learning engineer salaries with other tech roles:

In comparison, software engineers earn an average of $110,638, while data scientists earn $117,212.

Machine learning engineers and AI developers tend to earn more than many other tech professionals, with salaries that reflect the high demand and specialized skills required for these roles.

According to Glassdoor, the national average salary for a software engineer is $110,638. This is a significant figure, but it's worth noting that machine learning engineers typically earn more.

The data scientist role also falls into a similar salary range, with a national average of $117,212. This is likely due to the fact that data scientists often work closely with machine learning engineers and AI developers.

DevOps engineers and full stack developers also have similar salary ranges, with averages of $115,666 and $108,730 respectively. While these figures are competitive, they're still lower than those for machine learning engineers and AI developers.

Here's a comparison of these tech roles in a table format:

Machine learning engineers are among the highest-paid professionals in the technology sector, with many earning six-figure incomes.

Their average annual salary in the U.S. is a whopping $96,000 at entry-level, and can range from $70,000 to $132,000.

This is notably above the U.S. real median personal income, making machine learning engineers a highly sought-after and well-compensated profession.

Even the lower end of this salary scale is impressive, and demonstrates the high value placed on machine learning engineers' skills in the job market.

Machine learning engineers in the U.S. can earn an average of $96,000 annually at entry-level, with potential earnings ranging between $70,000 and $132,000.

Several factors can impact the salary of a machine learning engineer or AI developer, including experience, education, skills, industry, company size, location, and job title.

Experience is a significant factor, as more experienced professionals generally command higher salaries. Education also plays a crucial role, with advanced degrees (MS or Ph.D.) in computer science or related fields often leading to higher pay.

Proficiency in cutting-edge ML techniques and programming languages can increase earning potential. Certain industries, such as finance and healthcare, may offer higher salaries for AI expertise.

Here's an interesting read: Generative Ai Education

Here are some key factors to consider when it comes to salary:

Your salary as a machine learning engineer can vary significantly based on several factors. Experience is a major influencer, with more experienced professionals commanding higher salaries.

Education also plays a crucial role, with advanced degrees in computer science or related fields often leading to higher pay. For instance, a master's degree or Ph.D. in machine learning or AI can significantly boost your earning potential.

Your skills are also a key factor, with proficiency in cutting-edge ML techniques and programming languages increasing earning potential. Python, one of the primary programming languages, is a must-master for machine learning engineers.

Industry is another significant factor, with certain industries like finance and healthcare offering higher salaries for AI expertise. For example, a machine learning engineer in the finance industry may earn more than one in a startup.

Company size also matters, with larger tech companies often offering higher salaries compared to startups or smaller firms. Location is another important factor, with salaries varying significantly based on the cost of living in different regions.

Job title also impacts salary, with specific roles like "Senior ML Engineer" or "AI Architect" commanding higher pay. Additionally, your proficiency in specific tools and programming languages can also impact your salary, with proficiency in Python, TensorFlow, and other similar tools being highly valued in the industry.

Here are some key factors influencing AI and ML salaries, in a nutshell:

Technical skills are a crucial factor in determining the salary of a machine learning engineer. Proficiency in programming languages, particularly Python, is essential as it's one of the primary languages used in machine learning.

Mastering other programming languages like Java, C, C++, JavaScript, R, Scala, and Julia can also increase a machine learning engineer's salary. Familiarity with machine learning frameworks such as PyTorch or Keras is also necessary.

A deep understanding of standard algorithms across various domains, including supervised learning, unsupervised learning, reinforcement learning, and deep learning, is also required. This knowledge can be gained by studying machine learning systems and algorithms.

Mastering specific technical skills such as TypeScript, Flask, and Docker can significantly increase a machine learning engineer's salary, particularly in sectors like healthcare startups.

Here's a list of technical skills that are essential for machine learning engineers:

Machine learning engineers in the U.S. can earn an average of $96,000 annually at entry-level, with potential earnings ranging between $70,000 and $132,000.

The job growth for artificial intelligence engineers, a role closely related to a machine learning engineer, is projected to be about 23 percent between 2022 and 2032, which is significantly higher than the average for all occupations.

The demand for artificial intelligence specialists, which includes machine learning engineers, has grown 74 percent annually over the past four years. This growth is likely to keep salaries competitive.

Here are some key salary ranges for machine learning engineers in the U.S.:

As the demand for specialized skills in areas like deep learning, natural language processing, and computer vision grows, so will the salaries of machine learning engineers.

Related reading: Applied Machine Learning and Ai for Engineers

Machine learning engineers in the U.S. can earn an average of $96,000 annually at entry-level, with potential earnings ranging between $70,000 and $132,000.

To maximize your earning potential, continuously update your skills by staying current with the latest ML algorithms and AI technologies. This will help you stay competitive in the job market.

Gaining experience with real-world projects is also crucial, as it allows you to build a strong portfolio showcasing your expertise. This can be a game-changer in salary negotiations.

Consider pursuing advanced education, such as a master's degree or Ph.D. in machine learning or AI, to increase your earning potential. This can also lead to more job opportunities.

Developing domain expertise in high-demand areas like healthcare AI or financial ML can also boost your salary. For example, machine learning engineers specializing in healthcare AI can earn higher salaries due to the high demand for their skills.

Building a strong network is essential, and can be done by attending conferences, contributing to open-source projects, and engaging with the AI community. This will help you stay connected with industry professionals and stay updated on the latest developments.

Recommended read: How Will Ai Affect Software Engineers

Negotiating effectively is also crucial, and can be done by researching salary benchmarks and being prepared to negotiate your compensation package. This will help you get the salary you deserve.

Here are some education resources to help you boost your salary:

By continuously expanding your knowledge and staying up-to-date with the latest developments in the field, you can position yourself for higher-paying job opportunities.