Navigating the machine learning engineer salary landscape? You’re in the right place. Entry-level positions start around $96,000 annually, with seasoned professionals earning $177,177 on average in 2024. This article unfolds the salary story for a machine learning engineer, discussing how experience, location, and company size shape these figures. No fluff, just facts—read on for a clear breakdown of what to expect in the remuneration for this cutting-edge role in the computer science field. For optimal viewing of our website, please ensure you are using an updated browser.
Machine Learning Engineer Salary Takeaways
Machine learning engineers are vital in AI system development, with a wide salary range influenced by role, location, industry, and company size.
Salaries for a machine learning engineer rise with experience, averaging at $146,762 for mid-level and $177,177 for senior levels, with high variance across geographies and industries.
A gender pay gap exists in the field, with men earning more than women overall, and continuous learning, networking, and mobility are key strategies for advancing machine learning engineering careers.
What does a Machine Learning Engineer do
In a data science team, a Machine Learning Engineer plays a vital role, while a Data Scientist often collaborates closely, performing the following tasks:
Designing and developing algorithms that allow machines to learn from data
Enabling machines to make intelligent decisions
Acting as the architects behind AI systems
Conducting experiments and tests
Performing statistical analyses
Implementing machine learning algorithms
The machine learning engineer role transcends individual work. They collaborate closely with other team members, particularly data scientists, serving as a bridge between those who create models for AI systems and those who construct and operate them. Given the burgeoning demand for AI across organizations and various industries, the machine learning engineer role is indispensable and highly sought after.
In comparison, a software engineer specializing in machine learning also enjoys lucrative opportunities, with salaries often comparable to or even exceeding those of machine learning engineers. This highlights the diverse career paths available to professionals with similar skill sets, emphasizing the high demand and rewarding nature of these roles.
What are the qualities of a good Machine Learning Engineer
To become a proficient machine learning engineer, one needs a blend of technical expertise and soft skills. From a technical perspective, they should possess strong programming skills, including proficiency in languages like Python and R, and a deep understanding of data structures and algorithms. Expertise in applied mathematics, such as linear algebra, probability theory, and statistics, is also vital. Moreover, they should be well-versed in machine learning algorithms and libraries, which are essential for selecting and implementing suitable models.
On the other hand, soft skills are equally crucial. ML engineers should have:
Excellent communication skills to collaborate with diverse teams
Strong problem-solving abilities to tackle complex and real-time challenges
A passion for continuous learning, considering the rapidly evolving nature of the field.
Common Pay Structure Explained
For machine learning engineers, the typical pay structure includes an average base salary, bonuses, profit sharing, Machineand stock options. The base salary constitutes the bulk of the compensation, while bonuses and stock options are performance-based and influenced by the company’s profitability and individual performance.
Keep in mind, of course, the composition of these components can significantly vary based on factors such as the company’s size, industry, and location.
Average Total Cash Compensation
The total cash compensation for a Machine Learning Engineer encompasses the base salary, cash bonuses, and stock compensation. To bring this into perspective, let’s consider Meta, previously known as Facebook. The estimated salary range for a Machine Learning Engineer at Meta lies between $231,000 and $338,000 annually. The base salary, which forms a significant part of this compensation, is reported as approximately $184,000 per year.
That’s not all. On top of the base salary, a Machine Learning Engineer at Meta can expect an average additional pay of around $92,000 per year, which includes bonuses, stock, and other forms of compensation. This clearly shows that the total cash compensation for a Machine Learning Engineer extends beyond the base salary, offering substantial earning potential.
What is the average Machine Learning Engineer salary: 2024?
In 2024, the average salary for a mid-level machine learning engineer is projected to be $146,762, while senior-level professionals are anticipated to earn an average of $177,177. However, these figures aren’t set in stone. They can fluctuate based on various factors, one of which is location. Areas like San Francisco and Seattle, renowned tech hubs, offer significantly higher wages. For instance, a senior machine learning engineer in Seattle can earn up to $256,928.
Another noteworthy trend is the average annual increase in machine learning engineer salaries. In 2024, this increase stands at 1.55%, slightly lower than the average salary increase in the tech industry, which is 2%. However, the salary minimum for a senior machine learning engineer saw a higher growth of 6% from the previous year.
The takeaway here is that while the average salary provides a benchmark, the actual earnings of a machine learning engineer can vary significantly based on factors such as experience, location, and industry. Therefore, it’s important to factor these variables when considering potential earning prospects in the field of machine learning.
Machine Learning Engineer Salary by Experience Level
Experience is a crucial determinant of a machine learning engineer’s salary. Here is a breakdown of average machine learning engineer salaries based on experience level:
Entry-level machine learning engineers: $96,000 per year
Mid-career professionals: $144,000 per year
Late-career professionals: upwards of $150,000 per year
As professionals progress in their careers, they not only gather more experience but also develop specialized skills, both of which contribute to their salary growth.
To gain a better understanding, we will explore each career stage – entry-level, mid-career, and late-career – discussing the salary prospects for each.
Entry-Level Salaries
For those just stepping into the field of machine learning engineering, the average salary in the United States is $96,000 annually, with a range spanning from $70,000 to $132,000. It’s important to note that even at the entry-level, machine learning engineers command respectable salaries, reflecting the high demand for their expertise. However, these figures can fluctuate depending on factors like location, industry, and the size of the company.
Mid-Career Salaries
As machine learning engineers advance in their careers, their salaries see a significant boost. Mid-career professionals in the United States can expect to earn between $99,000 to $180,000, averaging approximately $144,000. To leverage this salary growth, a mid-career machine learning engineer should focus on developing a range of skills, including programming, data analysis, and domain specialization.
In addition, practical experience through actual problem-solving is essential for standing out and growing their salary, with verification successful waiting to be applied in real-life situations.
Late-Career Salaries & Senior Machine Learning Engineer Salaries
The earning potential continues to rise for late-career machine learning engineers. Here are some salary ranges for a machine learning engineer in the United States:
Typically earn between $115,000 to $204,000 annually
Professionals holding senior or principal engineering titles with at least 7 years of experience can expect around $153,820 per year
The highest reported salary for machine learning engineers can go up to $267,113.70
These figures may vary depending on factors such as experience, location, and benefits.
How Much Does a Machine Learning Engineer in Small, Medium, and Large Companies?
The company’s size significantly influences a machine learning engineer’s salary. Generally, larger companies with more resources at their disposal tend to offer higher salaries. These companies often have more complex projects that require a higher level of expertise, justifying the higher compensation. On the other hand, smaller companies may not offer as high salaries, but they often provide opportunities for engineers to work on a wider variety of projects and take on more responsibilities, which can be beneficial for career growth.
However, it’s not just about the size of the company. Other factors such as the company’s location, the industry it operates in, and the specific role of the machine learning engineer within the company can also significantly influence salary levels.
What was the average Machine Learning Engineer salary by company size: 2023?
Looking back at 2023, we see a similar trend where the size of a company had a significant impact on the salaries of machine learning engineers. Larger companies, especially those located in big tech- hubs, generally offered higher salaries due to their higher revenues and the complex nature of the projects they handle. However, smaller companies also offered competitive salaries, particularly those in high-demand sectors like information technology and healthcare.
In the end, the compensation greatly depended on a mix of factors, including the engineer’s role, experience, location, and the company’s industry.
Top-Paying Industries for Machine Learning Engineers
While the size of a company and location can impact a machine learning engineer’s salary, the industry in which they work is another important determinant. Some of the top-paying industries for a machine learning engineer in the United States include:
Information Technology
Human Resources & Staffing
Personal Consumer Services
Retail & Wholesale
Energy, Mining & Utilities
However, the IT, Healthcare, and Finance sectors stand out in terms of offering lucrative salaries and exciting opportunities. Let’s delve deeper into these industries.
Information Technology
The Information Technology industry is a top payer for machine learning engineers. Companies like Google, Amazon, and Facebook, known for their innovative tech solutions, offer competitive salaries. For instance, 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.
Given the rapid advancements in technology and the growing demand for AI solutions, the IT industry offers ample opportunities for a machine learning engineer to thrive.
Healthcare
The healthcare industry is another top payer for machine learning engineers, offering an average annual salary of $125,558. Specifically, healthcare startups, where the application of machine learning can lead to innovative solutions, offer an average salary of $114,806 per year. However, salaries can vary dramatically, with a range from $27,000 to $215,000, influenced by factors such as location, experience, and company size.
Nonetheless, at the top of the market, machine learning engineers can earn as much as $171,278 annually.
Finance
The finance industry is increasingly incorporating machine learning expertise to innovate and enhance services. A machine learning engineer in the finance industry 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.
What are the US states with the highest Machine Learning Engineer pay
Geographical location significantly impacts a machine learning engineer salary. Certain US states, known as tech hubs, offer higher salaries due to the concentration of tech companies and the high cost of living. While specific figures vary, it’s clear that states like California, New York, and Washington, home to tech giants like Google, Amazon, and Microsoft, consistently rank among the highest paying states for machine learning engineers.
California: Machine learning engineer salaries in California average around $175,000, with top earners making upwards of $250,000 in tech hubs like Silicon Valley and San Francisco.
New York: In New York, Machine Learning Engineer salaries are approximately $165,000, with potential to earn higher in New York City’s competitive market.
Washington: With companies like Amazon and Microsoft headquartered here, Washington state offers an average Machine Learning Engineer salaries are around $160,000.
Texas: The growing tech scene in cities like Austin and Dallas sees Machine Learning Engineer salaries of $150,000.
Massachusetts: Home to a bustling biotech industry and renowned academic institutions, Massachusetts offers an average salary of $155,000 for Machine Learning Engineer salaries.
Illinois: In Illinois, particularly in the Chicago area, Machine Learning Engineer salaries average around $145,000.
Essential Computer Science Skills and Qualifications for Machine Learning Engineers
Certain skills and qualifications are fundamental to excel as a machine learning engineer. Technical proficiency is paramount, with skills like proficiency in programming languages, understanding of machine learning algorithms, and familiarity with cloud platforms being critical. Specialization in areas such as deep learning and natural language processing can also enhance a machine learning engineer’s marketability.
However, technical skills aren’t the only requirement. Equally important are soft skills like communication, teamwork, and problem-solving capabilities. Additionally, pursuing specializations or skill set-specific programs such as coding boot-camps or obtaining relevant certifications can be beneficial for career advancement.
Let’s delve deeper into the technical skills, soft skills, and certifications that can set a machine learning engineer apart.
Technical Skills
A machine learning engineer’s toolkit should be filled with a variety of technical skills. Some essential skills include:
Python, one of the primary programming languages that a machine learning engineer must master
Other programming languages like Java, C, C++, JavaScript, R, Scala, and Julia
Proficiency in using machine learning frameworks such as PyTorch or Keras
Familiarity with distributed computing and cloud platforms like Azure
Moreover, a machine learning engineer should have a deep understanding of standard algorithms across various domains, including machine learning systems such as:
supervised learning
unsupervised learning
reinforcement learning
deep learning
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.
Soft Skills
While data science and technical software engineering skills lay the groundwork, soft skills ensure that machine learning engineers can effectively collaborate and communicate within a team and with stakeholders. Effective communication is vital as machine learning engineers often need to explain complex technical concepts in a way that non-technical team members can understand. They must also collaborate effectively with data scientists, requiring clear and concise communication to effectively combine technical insights with practical applications.
Furthermore, they often interface with business leaders, necessitating the ability to translate complex technical details into accessible language that supports decision-making, which is one of their key job responsibilities.
Certifications and Education
In terms of education, a bachelor’s degree in a relevant field is generally the minimum requirement for machine learning engineers jobs, with many roles requiring a master’s degree. Certifications provide specialized training on crucial industry-related aspects of machine learning, from algorithms to tools and real-world applications.
Nearly every top employer looks for candidates who continuously improve their knowledge and expertise in machine learning through recognized certifications and staying updated on new techniques. Such credentials can significantly enhance career prospects and earning potential.
Machine Learning Engineer Salary: Men vs Women
The pervasive issue of the gender wage gap is not exempt in the field of machine learning engineering. A study by O’Reilly found that men working in AI and data science alone, which includes machine learning positions, earn an average salary of $150,000 per year, while women earn $126,000 on average. This disparity persists despite women in AI and data science fields often having higher education levels than men, across similar job titles and educational achievements.
At the executive level, the gender pay gap is even more pronounced, with women earning $163,000 compared to men’s $205,000 – a striking 20 percent difference in median total pay. Furthermore, the gender pay gap in technology varies by state, with differences exceeding $15,000 in some cases, and women in New York and California earning significantly less than their male counterparts in terms of median total pay.
It is crucial to address these disparities to ensure equitable pay and opportunities in the field of machine learning engineering.
What is the outlook for Machine Learning Engineer pay?
Looking forward, machine learning engineers have a promising future. Here are some key points to consider:
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.
With such high demand for their technical expertise, artificial intelligence engineers can command six-figure salaries.
Therefore, in the field of computer science, machine learning engineering remains a promising career path from a financial perspective.
Who Are the Famous Machine Learning Engineers?
Numerous influential figures in the field of machine learning engineering and software engineering have significantly contributed and expanded the realm of possibilities. These individuals not only excel in their technical prowess but also in their ability to inspire and lead others in this exciting field.
Among these luminaries is Geoffrey Hinton, known for his work on neural networks and deep learning, and a recipient of the Turing Award. He is often referred to as a ‘Godfather of AI’.
Another notable figure is Andrew Ng, co-founder of Coursera and former leader of Google Brain, who is a major advocate for democratizing deep learning and has influenced a large audience through his online courses.
Other inspiring figures include Fei-Fei Li, a professor at Stanford University known for her leadership in AI research and for pioneering work with ImageNet, and Yann LeCun, VP & Chief AI Scientist at Facebook and a recipient of the 2018 ACM Turing Award for his work in AI. These individuals, along with many others, have significantly shaped the field of machine learning engineering and continue to inspire new generations of engineers.
Tips for Boosting Your Machine Learning Engineer Salary
Beyond the average salaries and trends, machine learning engineers can undertake specific actions to enhance their earnings. These strategies include building a strong network, continuously learning and developing skills, and being open to job mobility and relocation. Let’s delve into each of these strategies in more detail.
Building an online presence on social platforms like LinkedIn and Twitter, as well as joining online communities, is crucial for networking in the machine learning field. Practical experience in applying machine learning to real-world situations is highly valued and can substantially increase salary prospects. A machine learning engineer can boost their salaries by actively learning new skills through various education resources, such as:
Online courses and tutorials
Books and research papers
Attending conferences and workshops
Participating in Kaggle competitions
By continuously expanding their knowledge and staying up-to-date with the latest developments in the field, a machine learning engineer can position themselves for higher-paying job opportunities.
Finally, sharing salary information on platforms like Glassdoor can help employers ensure fair compensation in the machine learning industry.
Networking and Industry Connections
Just like in other fields, networking plays a vital role in the career growth of machine learning engineers. It helps expand social connections and engage with industry influencers, which can lead to better job opportunities and improved salary prospects.
Attending industry-specific events like conferences, seminars, and courses offer valuable networking opportunities and enhances one’s understanding of the machine learning field. Cultivating industry connections through networking can open doors to improved job opportunities, which are often linked to higher salary prospects.
Continuous Learning and Skill Development
Continuous education is a necessity in a swiftly changing field like machine learning. Staying abreast of new tools, platforms, and techniques is crucial to remain competitive in the job market. Learning new programming languages can significantly enhance a machine learning engineer’s usefulness and career prospects.
Developing expertise in emerging areas of machine learning, such as reinforcement learning, can lead to higher salaries and specialized positions. Active participation in workshops, seminars, and certifications can propel machine learning engineers to higher-level roles and better compensation.
Job Mobility and Relocation
Other factors that can influence a machine learning engineer’s salary include job mobility and relocation. Moving to a tech-hub city can offer better job opportunities and potentially higher salaries. Likewise, being open to job mobility, such as switching companies or roles, can lead to higher-paying opportunities.
Therefore, while the comfort of a familiar environment is appealing, machine learning engineers should consider job mobility and relocation as potential strategies to explore for boosting their salaries.
In this comprehensive guide, we delved into the intricate world of machine learning engineering, exploring various facets that influence the salaries of these professionals. We discussed the role of machine learning engineers, the skills and qualifications they need, and how factors like experience, location, company size, and industry can impact their salaries. We also touched upon the gender wage gap in this field and the future prospects for machine learning engineer salaries.
In conclusion, machine learning engineering is a dynamic and lucrative career path. As AI continues to revolutionize various sectors, the demand for skilled machine learning engineers will only grow, offering promising career prospects and competitive salaries. Therefore, whether you are an aspiring machine learning engineer or an experienced professional, the future is bright, filled with exciting opportunities and challenges that will push you to continually learn, innovate, and excel in this field.
How much do machine learning engineers make?
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. Even the lower end of this scale is notably above the U.S. real median personal income.
What do machine learning engineer do?
Machine learning engineers build and develop artificial intelligence systems that learn from data to make predictions and improve accuracy. They also play a critical role in researching, designing, and maintaining AI systems within the data science team.
Is machine learning engineer highest paid?
Yes, machine learning engineers are among the highest-paid professionals in the technology sector, with many earning six-figure incomes. Various job titles in machine learning, such as Machine Learning Engineer and Data Scientist, are known for commanding high salaries.
What is the average salary of a machine learning engineer in 2024?
The average salary for mid-level machine learning engineers is expected to be $146,762, while senior-level professionals are anticipated to earn an average of $177,177 in 2024.
What skills are required to be a successful machine learning engineer?
To be a successful ml engineer, you need strong technical skills such as programming and understanding of machine learning algorithms, as well as familiarity with cloud platforms. Soft skills like communication, teamwork, and problem-solving capabilities are also crucial.
