The average salary of a machine-learning

In the evolving landscape of technology, the machine learning engineer’s role stands out as a highly coveted position. Marrying the principles of computer science with predictive analytics has revolutionized several sectors. One might wonder: What is the average salary of a machine-learning in today’s market? How does it stack up against salaries in other tech-centric roles?

This article aims to shed light on the average salary of a machine-learning engineer in AI Jobs and the various elements that shape it.

Defining a Machine Learning Engineer

Authorized with the task of seamlessly melding machine learning algorithms into platforms, systems, and applications, a machine learning engineer leverages intricate statistical methods to craft cutting-edge solutions to intricate issues. Machine learning engineers’ motivation is to design and deploy sizable machine learning-driven systems, which sets them apart from data scientists who delve deeply into data to extract meaningful patterns.

What do machine learning engineers do?

1. Design and Develop Machine Learning Models

Machine learning engineers design algorithms that help machines identify patterns in data. They employ techniques from neural networks, regression, decision trees, and more to create models that can make predictions or automate decision-making.

2. Data Analysis and Processing

Before feeding data into machine learning models, it often needs to be cleaned, transformed, and structured. Engineers work with vast datasets, preparing them for training and testing.

3. Deployment and Expansion

After crafting a machine learning algorithm, engineers are tasked with ensuring its applicability in real-world scenarios. This involves embedding the algorithm within prevailing systems and enhancing its capacity to process extensive data volumes.

4. Assessing and refining models

Regularly, engineers gauge the efficiency of their algorithms. Employing diverse evaluation criteria, they determine precision. Using this feedback, the algorithm undergoes improvements to boost its efficacy.

5. Keeping Abreast of Evolving Technology

Machine learning is a dynamic domain. To maintain the relevance of their solutions, engineers must stay informed about the latest advancements, methodologies, and digital tools in the industry.

Team Endeavors

It’s commonplace for machine learning engineers to join forces with data analysts, software creators, and other key members within a corporation. Through collective efforts, they transform data-centric findings into practical enterprise tactics.

What is the average salary of a machine learning engineer?

The average salary of a machine learning engineer globally is approximately $110,000 USD per year. This figure varies depending on a number of factors, including experience, location, and industry.

The average salary of a machine-learning engineer in different countries

  • United States: $160,140 USD
  • United Kingdom: £63,489 GBP
  • India: ₹8,55,725 INR
  • Canada: $101,657 CAD
  • Australia: AUD 132,993

The average salary of a machine-learning engineer with experience

  • Less than 1 year: $120,571
  • 1-3 years: $136,382
  • 3-5 years: $153,147
  • 5-7 years: $166,881
  • 7+ years: $178,077

Which companies offer machine-learning engineer jobs?

Which companies offer machine learning engineer jobs?

Here are some of the top companies that offer machine learning engineer jobs:

  • Google
  • Meta
  • Amazon
  • Microsoft
  • Apple
  • IBM
  • Intel
  • Nvidia
  • Salesforce
  • Netflix
  • Airbnb
  • Uber

Factors Influencing the Average Salary of a Machine Learning Engineer

Geographical Location

The salary of a Machine Learning Engineer can vary significantly based on the region or country they work in. For instance, salaries in the tech hubs of Silicon Valley, USA, are likely to be higher compared to developing countries. However, when adjusted for the cost of living, the differences might narrow down.

Years of Experience

A newbie in the field may start at a base salary, but as they accumulate experience and refine their expertise, their compensation sees a substantial increase. Senior machine learning engineers or those with specialized knowledge can command significantly higher salaries.

Industry and Application

The industry a machine learning engineer works can also be a determining factor. For example, the finance and healthcare sectors, which heavily rely on accurate predictions and data, might offer a higher salary compared to other sectors.

Education and Specializations

While a bachelor’s degree might be the entry point, having advanced degrees like a Master’s or Ph.D., especially from reputed institutions, can significantly boost the salary. Additionally, certifications or specializations in niche areas can also influence the pay scale.

Skills Required for a Machine Learning Engineer Job

Skills Required for a Machine Learning Engineer Job

A Machine Learning Engineer is pivotal in designing and implementing algorithms that allow computers to learn from data. To excel in this position, one needs a blend of technical and soft skills. Here’s a concise list:

  1. Technical Proficiency: Understanding programming languages, especially Python, R, and Java, is essential.
  2. Statistical Analysis: Ability to analyze vast datasets and draw insights.
  3. Algorithm Knowledge: Familiarity with machine learning algorithms like neural networks, decision trees, and regression.
  4. Data Modeling & Evaluation: Skill in creating accurate data models and evaluating their performance.
  5. Advanced Mathematics: Strong foundation in calculus, linear algebra, and statistics.
  6. Software Engineering: Proficiency in software design, testing, and debugging.
  7. Big Data Technologies: Experience with platforms like Hadoop and Spark can be beneficial.
  8. Cloud Platforms: Familiarity with cloud services such as AWS, Google Cloud, and Azure.
  9. Continuous Learning: Machine learning is a rapidly evolving field. An aptitude for continuous learning and staying updated with industry trends is crucial.
  10. Problem-Solving: Ability to approach complex challenges methodically and come up with effective solutions.
  11. Communication Skills: Capability to explain complex models to non-technical stakeholders
  12. Teamwork: Collaborative skills to work seamlessly with data scientists, engineers, and other professionals.

The Future Outlook

The demand for machine-learning Engineers shows no signs of slowing down. As businesses across the globe recognize the potential of AI and machine learning, the value placed on these professionals is only set to increase. This trend suggests that the Average Salary of a Machine Learning Engineer might see a steady rise in the coming years.


What does a machine learning engineer primarily do?

A machine learning engineer designs, develops, and implements algorithms allowing machines to learn from and make decisions based on data.

How does a Machine Learning Engineer differ from a Data Scientist?

While both roles work with large data sets and algorithms, a data scientist typically focuses on deriving insights from data. In contrast, a machine learning engineer focuses on designing and implementing scalable machine learning applications.

What programming languages should a machine learning engineer be familiar with?

Python and R are the most common languages in the field. However, proficiency in Java, Scala, and others can also be beneficial, depending on the applications and platforms used.

Are machine learning engineers only required in the tech industry?

No, they are valuable across multiple industries, including healthcare, finance, retail, and more, due to the widespread applicability of machine learning solutions.


In conclusion, the average salary of a machine-learning engineer can vary due to numerous elements. Nevertheless, the financial rewards associated with this profession are undeniably attractive. As our global community gravitates towards decisions backed by data and seeks greater automation, the prominence of machine learning engineers is set to grow. They remain pivotal in crafting the technological future and are, consequently, aptly remunerated for their skills.


Similar Posts