Artificial intelligence (AI) and machine learning (ML) are evolving quickly. Artificial intelligence got a slow start, considering the first AI program was written in 1951, and it went through a few “AI winters” where not much progress was made. But AI is on a roll now.
Almost every company and industry uses some form of AI and machine learning to build better products and provide better services to their customers. And almost all of them are looking for AI ML engineers to get the work done and are willing to pay them well, but an AI ML engineer’s salary can vary widely depending on many factors. In this article, we’ll look at some of those factors and what you can do to boost your AI ML engineer salary.
Who is an AI ML Engineer?
An AI ML engineer spends the day training a computer how to think like a human by building machine learning and artificial intelligent systems. They know various programming languages, statistical analysis, data structures, and algorithms.
Since machine learning is used in many industries, an AI ML engineer might work in any of them, including healthcare, finance, and transportation. Since AI development is a team process at most companies, they will work with data scientists, project managers, and other engineers to do their job.
What Does an AI ML Engineer Do?
AI ML engineers are responsible for designing, developing, and testing AI and ML systems. They create algorithms and models that can analyze data, recognize patterns, and make predictions based on that data.
Here are some of the tasks an AI ML engineer might be expected to complete:
- Designing AI and ML systems: They use programming languages to develop algorithms to process data and create machine learning models.
- Developing and testing AI models: Once machine learning models have been created, the engineer trains those models on historical data and tests the results with cross-validation techniques to ensure accuracy.
- Building natural language processing systems: Machine learning engineers use techniques like sentiment analysis, speech recognition, and language translation to create systems that can communicate with humans.
- Staying up-to-date with the latest developments in AI and ML: New machine learning techniques are developed all the time, and the AIML engineer may read papers or participate in online communities to discover new trends in the field.
Top AI ML Engineer Jobs
Artificial intelligence is a broad field that relies on many specialized technologies and has been applied to various industries in many different ways. Many jobs are available to qualified AI/ML professionals in the machine learning and AI field, each with its own specialties. Here are some common ones:
AI Research Scientist
These AI professionals do research and experiments to develop new AI and machine learning technologies by creating algorithms, designing models, and developing systems that can learn and adapt.
Machine Learning Engineer
A machine learning engineer creates and maintains systems that can learn and adapt based on large datasets using programming languages such as Python, Java, or C++.
Data scientists design and develop algorithms and models to identify patterns and trends in data. And they use these insights to inform business decisions.
Software engineers work with other professionals, such as project managers and software architects, to understand the requirements of a project and develop software solutions that meet those requirements.
Big Data Architect
A big data architect works with other developers and data experts to understand business needs and design solutions that can handle vast amounts of data.
Best Countries for AI ML Engineer Salaries and Jobs
An AIML engineer’s salary can depend on a lot of factors. One crucial component is location, starting at the country level. In more technologically advanced countries, the pay tends to be higher. Here are some of the top-paying countries for machine learning professionals, according to Analytics Insight:
- United States: average salary of $145,000 per year
- China: average salary of CN¥450,000 per year
- Japan: average salary of ¥6,404,246 per year
- South Korea: average salary of ₩62,692,165 per year
- India: average salary of Rs.11 lakhs per year
- Germany: average salary of €75,000 per year
- Canada: average salary of $85,000 per year
- Sweden: average salary of 460,000 KR per year
- United Kingdom: average salary of £50,000 per year
- Spain: average salary of €55,000 per year
AI and ML Engineer Salary by Region and State
While the United States has some of the highest-paying AI and ML jobs in the world, where you get a job in the US can affect the salary. According to Indeed, these are the states that pay AI professionals more than the average:
- California: 14 percent higher
- Washington: 10 percent higher
- New York: 6 percent higher
- North Carolina: 5 percent higher
The rest of the states either pay the national average or less. As it turns out, most of the highest-paying cities for machine learning professionals are also in the highest-paying states, but some aren’t. Here are the cities where professionals can earn the best AI ML engineer salary, also courtesy of Indeed:
- New York, NY: $193,066
- Cupertino, CA: $177,841
- San Francisco, CA: $160,113
- San Jose, CA: $159,198
- Santa Clara, CA: $157,873
- San Diego, CA: $141,094
- Pittsburgh, PA: $139,977
- St. Louis, MO: $132,026
- Reno, NV: $122,320
Also Read: What are Today’s Top Ten AI Technologies?
Top Companies and Recruiters Hiring AI ML Engineers
There is a reason why you can find a higher AI ML engineer salary in California or Washington. That is where many of the biggest tech companies in the US are located. Here are some of the top tech companies that are always looking for new AI and machine learning talent, according to Glassdoor:
- Google: Google was founded in 1998 and always looks for engineers who understand machine learning, natural language processing, and deep learning.
- Meta: The company responsible for Facebook is working on its own AI technology.
- LinkedIn: LinkedIn uses AI to sort and process the massive amounts of job listings and people’s data they collect daily.
- Apple: Apple is using AI to make their devices and apps smarter.
- Intel: At Intel, AI is not only about software but also about developing better AI-capable hardware.
- Amazon: Amazon uses AI in Alexa and Amazon Go and provides AI-based tools for developers.
How to Boost Your AI Machine Learning Salary
While an AI machine learning salary will depend on the company you work for, its location, and the experience you’ll build on the job, there are some things you can do to boost your AI and ML salary potential. Here are some things you can do to get more pay as an AI engineer:
- Get a degree: Most machine learning jobs require a bachelor’s degree, but some require a master’s or Ph.D., which will pay more.
- Pursue a leadership role: If you can see yourself in management someday, take a leadership course and work toward a leadership role.
- Build your portfolio: Having examples of your work shows recruiters you can do the work and are interested in it enough to do it without pay.
- Keep up to date: Today’s AI is not the same as yesterday’s AI. Learn new techniques, and make sure to add your experiments to your portfolio.
- Enroll in a top-rated AIML certification program: The right certification will get you noticed. Read on to find out how.
Want to Get into the AI/ML Field? You Have Great Options
If you’re planning a career in machine learning and AI, you’re entering a field where you will be in demand and be paid well. How well you are paid depends on various factors, including location and the company you work for. But there are ways you can boost your AI and machine learning salary, including getting a higher-level degree, keeping up on AI and ML trends, and pursuing a management role.
One of the best ways to boost your AI ML engineer salary is to enroll in a top-rated AI ML bootcamp that provides a valuable certificate upon completion. Global AI and machine learning experts lead the classes, who will guide you through 25+ real-world projects in integrated labs. By the end of the course, you will understand the workings of computer vision, speech recognition, natural language processing, neural networks, and much more.