Machine Learning Engineer Salary in India and Abroad

Market Research Future estimates that the global machine learning market will grow $30.6B by 2024, attaining a CAGR of 43%. The demand for machine learning engineers is constantly increasing, positively affecting these professionals’ salaries. If you plan to make a career in machine learning, then knowing the expected salary for the job is beneficial. In this article, we will cover machine learning engineer salaries in 2023.  

Who is a Machine Learning Engineer?

An AI professional who designs, builds, and implements machine learning systems and models is known as Machine Learning Engineer. ML engineers have excellent educational backgrounds in statistics, mathematics, data science, and computer science. They can skillfully use programming languages (Java, C++, or Python) for valuable professional outcomes. They can effectively use programming languages like Python, C++, or Java.

An ML Engineer works closely with software developers and data scientists. They develop and operate systems and models for machine learning that can learn from data and predict or decide. 

Many industries, such as healthcare, finance, e-commerce, and more, highly demand machine learning engineers. ML engineers are the best-paid groups in the workforce due to their specialization specificity.

Also Read: Java vs Python – Which is a Better Language for Data Scientists?

What Does an ML Engineer Do?

ML Engineer salary depends on the work and responsibilities they have. Enlisted below are some everyday responsibilities for these professionals: 

• Designing and Implementing Machine Learning Models: The role involves planning and executing machine learning models that can analyze data and accurately forecast outcomes or make decisions.
• Algorithm Development and Optimization: Algorithms are designed and optimized for machine learning models by machine learning engineers. Such algorithms achieve better speed, scalability, and accuracy.
• Data Preparation and Preprocessing: Machine Learning Engineers work with large datasets and prepare and preprocess the data to ensure it is clean, accurate, and suitable for training the machine learning models.
• Model Deployment and Integration: Such professionals are involved in integrating machine learning models into more extensive software systems and deploying them in real-world settings.
• Collaboration with Cross-functional Teams: Machine Learning Engineers collaborate with teams (software developers, data scientists, and business stakeholders) to ensure ML models align with business goals and meet standards.
• Model Monitoring and Maintenance: An ML engineer’s crucial responsibility is to monitor and adjust machine learning models regularly to ensure accuracy and relevance.

Factors Affecting Machine Learning Engineer Salary

The most common factors affecting the salary of an ML Engineer include the following:

• Education: Advanced degree holders in computer science, statistics, mathematics, or data science get higher salaries than individuals with a bachelor’s degree.
• Experience: Individuals with more experience and diverse skill sets may get highly paid compared to beginners in the field.
• Company Size and Location: Professionals working for larger companies or in premium locations may obtain higher salaries when compared to those working for smaller companies or those in low-cost areas.
• Industry Sector: Certain industries (finance, healthcare, or technology) highly demand machine learning engineers. Such industries pay higher salaries to ML engineers when compared to those who work in less-demanding ones.

Also Read: Step-by-Step Guide to Become a Data Scientist in 2023

Current Job Market for Machine Learning Engineers

Machine Learning Engineers are highly in demand in the job market of 2023. As industries increasingly rely on data-driven decision-making and automation, the demand for Machine Learning Engineers has grown significantly. 

In the current scenario, there are numerous responsibilities that Machine Learning Engineers are attending to. The technological tendencies design, construct and implement machine learning models in production domains. ML engineers work on different stages of the machine learning pipeline and demand a high machine learning salary.

Depending on the company, location, and experience level, $155,322 is the average annual salary for Machine Learning Engineers in the United States. The machine learning salary for a professional may range from $97,090 (entry-level) to as high as  $181,000 (senior-level). 

The top companies hiring ML engineers and offering a good salary are eBay, Bain & Company, Engtal, Tapjoy, and Snap Inc. Also, the highest machine learning salary-paying industries for ML engineers are healthcare, finance, and technology. According to the latest ratings, 61% of Machine Learning Engineers in the United States experience salary satisfaction.

In the coming years, there will be high demand for machine learning engineers as businesses seek to use this technology for innovation and gain a competitive edge.

Average Salaries for ML Engineers in Different Regions and Industries

Machine Learning Engineer Salary in Different Regions

The table below shows the average salaries for Machine Learning Engineers in May 2023 in different regions according to data from Indeed and Glassdoor:

Machine Learning Engineer Salary in Different Industries

The table below shows the average salaries for Machine Learning Engineers in May 2023 in different industries according to Indeed and Glassdoor:

Note: These are general averages of machine learning engineer salary data which may vary based on many factors.

Career Growth Opportunities for Machine Learning Engineers

Many career growth opportunities exist for machine learning engineers due to the high demand for ML skills in different fields.

Advancement Opportunities for Machine Learning Engineers

Some potential advancement opportunities include the following:

• Senior Machine Learning Engineer: A Machine Learning Engineer with several years of experience (10+ years of experience) advances to senior roles. A senior ML engineer may mentor junior staff, lead teams, and handle complex assignments.
• Machine Learning Architect: With vast experience in machine learning architecture and model design, an ML engineer may transcend to an ML Architect role. The role of Machine Learning architects is to create complex machine learning systems on a large scale.
• Machine Learning Manager: Individuals with strong leadership skills and team management experience may transcend to become a machine learning manager who oversees numerous machine learning teams and projects.
• Director of Machine Learning: When merged with several years of experience, the management position advances to the Director of Machine Learning role. The director looks after the entire machine-learning strategy of the organization and leads multiple teams.
• Entrepreneurship: Many Machine Learning Engineers establish their ventures, utilizing their knowledge to develop cutting-edge machine learning offerings.

Impact of Additional Skills and Certifications on Salary Levels

Examples of the skills and certifications that may influence salary include:

• Machine Learning Platforms: Certain certifications make ML engineers more marketable to potential employers. Popular machine-learning platforms include PyTorch, Scikit-learn, TensorFlow, etc.
• Big Data Processing: Certifications and skills in big data processing technologies indicate an ability to work with large-scale data sets. Some important ones include Spark and Apache Hadoop.
• Cloud Computing: Certifications and skills in cloud computing platforms, namely Amazon Web Services (AWS), Google Cloud, and Microsoft Azure, are becoming increasingly popular.
• Natural Language Processing (NLP): Certifications and skills in NLP technologies showcase a tendency to function with unstructured text data. NLTK and spaCy technologies are NLPs that hold importance in chatbots and language translation systems.

Machine Learning Engineers with additional certifications and skills in the AI field promise to add more value to organizations. Hence, they can command a better pay scale than those without and boost their advancement opportunities toward career growth.

Future Outlook for Machine Learning Engineers

Here are a few reasons why machine learning salary is skyrocketing and indicating a bright future outlook for ML engineers:

• Continued Growth: Machine learning is expected to grow due to technological advancements, increased data accessibility, and demand for automated decision-making.
• Advancements in AI: Machine learning engineers are essential for creating and deploying AI technologies, which have the potential to have a significant impact on industries.
• Emerging Industries: New career prospects for machine learning engineers are being created using machine learning in emerging industries.
• High Demand: As more organizations implement machine learning technology, there will likely be a rise in the demand for qualified machine learning engineers.
• Increasing Salaries: Machine learning engineers are in high demand, making them a lucrative career path by increased pay scale.

How is Machine Learning Revolutionizing Industries?

Machine learning is revolutionizing various industries by enabling businesses to obtain insights and make predictions from massive amounts of data. Below are a few examples of how industries are transforming via machine learning.

• Healthcare: Analysis of medical data to find patterns and insights that can assist in diagnosing diseases.
• Transportation: The development of autonomous vehicles designed to make decisions and learn about driving through sensors.
• Finance: Analysis of financial data, identifying trends and patterns, making market movement predictions, credit risk, and fraud detection.
• Retail: Analysis of customer data to personalize shopping experiences, identify preferences and behaviors, and improve supply chain management.
• Agriculture: Analysis of weather and soil data to regulate crop yields and enrich resource administration.
• Manufacturing: Optimize manufacturing processes in factories by identifying potential equipment losses and improving quality management.
• Energy: Optimize energy distribution and production, anticipate equipment breakdowns and reduce energy usage.

Best Countries for ML Engineer Jobs

1. United States: Home to Silicon Valley and numerous tech giants, the U.S. offers a vast number of job opportunities, research institutions, and high salaries.
2. Canada: Known for its welcoming immigration policies and strong AI research, Canada boasts top universities and tech hubs like Toronto and Montreal.
3. United Kingdom: With renowned universities and a thriving tech ecosystem in cities like London, the UK provides excellent opportunities for machine learning professionals.
4. Germany: A leader in manufacturing and innovation, Germany has a growing AI and machine learning sector in cities like Berlin and Munich.
5. France: Paris is emerging as a European tech hub with a focus on AI, and France offers a vibrant research community and a competitive job market.
6. Australia: Major cities like Sydney and Melbourne have a growing tech scene, and Australia’s quality of life and research opportunities attract machine learning talent.
7. Switzerland: Known for precision engineering, Switzerland has AI research institutions and global companies offering well-paying positions.
8. Netherlands: Amsterdam and other Dutch cities are hubs for tech startups, and the country’s strong economy provides numerous machine learning job opportunities.
9. Singapore: Singapore’s strategic location in Asia, along with government initiatives to promote AI, makes it a hotbed for machine learning roles.
10. China: With rapid technological advancements, China’s major cities like Beijing and Shanghai have a burgeoning demand for machine learning expertise.

End Note

In conclusion, ML engineering offers substantial earning potential for professionals with the necessary skills and expertise. With average salaries ranging from $90,000 to $150,000 per year, ML engineers are among the highest-paid individuals in the data science domain. Individuals can consider upskilling through our BlackBelt Data Science program to excel in this field and maximize their earning potential. By acquiring advanced knowledge and hands-on experience, aspiring ML engineers can enhance their value in the job market and increase their earning potential. Whether starting your career in ML engineering or aiming to progress further, investing in continuous learning and professional development can significantly contribute to a rewarding and lucrative career in this exciting field.

Frequently Asked Questions