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Are you aiming for machine learning positions? Machine Learning is a rapidly expanding subject with a high need for professionals in the United States. According to researchers at the Oxford Internet Institute, from 2023 to 2027, the demand for ML specialists will increase by 40%. As far as machine learning professions are concerned, the machine learning salary is an ongoing quest of many aspirants and ML professionals. Machine Learning Engineer Salaries are affected by several factors like skill sets, experience, location, and so on.
So, let us delve into this article to find an ML engineer's salary in the United States.
Here is what we will cover:
Recruiters are looking for applicants with current and in-demand skills such as deep learning, natural language processing (NLP), Python, and computer vision to work as machine learning engineers in the United States.
High-paying machine learning engineer skills in the United States that boost the ML Engineer's salary are:
Knowing which skills offer better pay can help you strategize your career progress and boost your growth substantially.
Experience is an important factor in deciding how much you can make as a machine learning engineer. Entry-level ML engineers typically earn less than the norm. However, a mid-career professional in this sector earns more.
For example, machine learning engineers with less than a year of expertise earn less than those with one to four years of professional experience. So, acquiring more experience in machine learning will help you earn a greater salary.
Each city has its own culture, demographics, and cost of life. As a result, the city in which people work might have a significant impact on how much they earn as a machine learning engineer. Several cities in the United States pay much more than the national average. Working there may help one find higher-paying jobs as an ML engineer at reputable companies.
The cities with the highest average salaries for the role of an ML engineer include the following:
Similarly, cities such as Chicago and Boston offer below-average earnings for this position.
The compensation of a machine learning engineer varies per company. It is determined by a variety of criteria, including the size of the organization, the work environment, the benefits provided, and so on.
Adobe (average compensation $197,997) and Meta (average pay $183,265) offer the best salaries for machine learning roles. Similarly, due to the nature of the job, some organizations give lower pay for this position. Lockheed Martin Corp (an average salary of $125,727) and MITRE (an average salary of $109,731) are two such organizations.
A machine learning engineer's income may also be affected by the industry in which they work. The value machine learning adds to the operations of tech organizations, financial institutions, healthcare providers, and e-commerce companies often translates into greater pay.
With the growing acceptability of remote work, machine learning engineers may discover opportunities to work for organizations in high-cost-of-living areas while living in lower-cost ones, which could affect their effective income.
To decide on fair and competitive compensation in your individual circumstances, you must examine these elements and perform extensive research. Remember that pay is only one component of total pay; perks, stock options, and work-life balance should all be addressed when evaluating job offers.
According to Indeed, the average base salary for a Machine Learning Engineer in the United States is $160,406 annually. It falls within a range from $104,454 - $246,329. Additionally, the average cash compensation is $22,592 per year.
The salary of a machine learning engineer is heavily influenced by experience. Due to expertise, skill development, and contributions to more complicated projects, entry-level engineers earn less than those with years of experience.
In the US, the average total income for a Junior Machine Learning Engineer is $114,400 per year. The average base salary of an Entry-level Machine Learning Engineer is $97,205 per year, and the additional pay is $17,195 per year.
In the US, the average total income for a Mid-level Machine Learning Engineer is $1,62,774 per year. The average base salary of a Mid-level Machine Learning Engineer is $1,40,182 per year, and the additional pay is $22,592 per year.
In the US, the average total income for a Senior Machine Learning Engineer is $1,85,416 per year. The average base salary of a Senior Machine Learning Engineer is $1,57,956 per year, and the additional pay is $27,460 per year.
Machine Learning Engineers' salaries are also affected by their location. Machine Learning Engineers in high-cost-of-living places should expect to earn more than those in small towns or rural areas.
Here is a list of the highest-paying cities for Machine Learning Engineers around the United States as of October 2023.
Machine learning engineers in FAANG (Facebook, Apple, Amazon, Netflix, and Google) companies often have a wide range of duties that revolve around designing and deploying machine learning models to address challenging issues.
The table below shows a comparison of the average annual Machine Learning Engineer Salary at FAANG Companies.
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According to Glassdoor, the Machine Learning Scientist's salary annually is estimated to be $1,66,990 per year in the United States.
In India, the Senior Machine Learning Engineer salary ranges between ₹ 7.2 Lakhs to ₹ 45.0 Lakhs annually. The average annual salary is ₹ 16.5 Lakhs.
Data science and machine learning are related but distinct disciplines. Data science adds structure to huge amounts of data, but machine learning learns from the data itself.
India is one of the top countries for ML Engineers due to the Indian government's adequate financial allocation. Other popular countries in ML recruitment include Japan, Germany, and South Korea.
Machine Learning is a rapidly expanding subject with a high need for professionals in the United States. Machine Learning graduates can work as Machine Learning Engineers, Data Scientists, Big Data Engineers, and Business Intelligence Analysts.
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