Note that this role can fluctuate, depending on the organization they work for or the size of their AI staff. The U.S. Bureau of Labor Statistics also notes that computer and information research scientist roles, which include AI engineers, saw an annual median wage of over $131,000 as of 2021. With this same job area projected to grow 21 percent by 2031, AI engineers can expect to see healthy financial compensation and job growth over the next decade. A cross between data scientists, software engineers and statisticians — AI engineers bring artificial intelligence products to life. Becoming an AI engineer requires basic computer, information technology (IT), and math skills, as these are critical to maneuvering artificial intelligence programs.
Programming languages are an essential part of any AI job, and an AI engineer is no exception; in most AI job descriptions, programming proficiency is required. Government agencies and defense organizations also employ AI engineers to work on applications such as national security, healthcare, and public services. In the finance and banking sectors, AI engineers contribute to fraud detection, risk assessment, and algorithmic trading.
What qualifications do I need to become an AI engineer in 2024?
Machine-gaining knowledge of algorithms now shapes or surpasses human abilities in many specialized responsibilities. Autonomous cars continue progressing toward full self-driving capability. Behind the scenes, powering these improvements are gifted AI engineering teams.
After all, with the proper training and experience, AI engineers can advance to senior positions and even C-suite-level roles. You’ll master fundamental concepts of machine learning and deep learning, including supervised and unsupervised learning, using programming languages like Python. R is commonly used for statistical software development, data analysis, and/or data visualization in AI. And C++ is known for its very fast processing speed, which is essential to the performance of complex machine learning models. Some people fear artificial intelligence is a disruptive technology that will cause mass unemployment and give machines control of our lives, like something out of a dystopian science fiction story.
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New techniques, improved neural architectures, faster processors and larger datasets relentlessly push performance boundaries yearly. But core AI engineering foundations remain essential—creative problem solving, data science fluency, ML expertise and coding proficiency. The US Bureau of Labor Statistics projects that the number of AI engineer jobs will increase by 21% from 2020 to 2030—much faster than the average for all occupations. Globally, estimates advise that the AI industry might be worth $1 trillion by 2028. AI is an expanding, global-converting area rich with career opportunities.
AI engineers receive an average salary range of $99,000 to $167,000 in the United States as of 2023, according to Glassdoor. Learning the ins and outs of AI on one’s own can get “overwhelming,” Abdullah said, especially if you’re in the really early stages of career development and want to narrow your interests down. She suggests finding a mentor who actively works in the industry, so they can give you a clear idea of what working in the space is actually like, and even help narrow down an area of focus. Becoming a successful AI engineer really comes down to an individual person’s willingness to learn, their passion for the industry and the opportunities they create for themselves. There is a projected job growth of 23 percent between 2022 and 2032, which is much faster than the average for all occupations [4]. According to Glassdoor, the average salary for an AI engineer is $115,623 in the United States as of March 2024[3].
Software Engineering and Programming Skills
The six months of applied learning include over 25 real-world projects with integrated labs and capstone projects in three domains that will validate your skills and prepare you for any challenges you must tackle. Here is a series of recommended steps to help you understand how to become an AI engineer. Consider enrolling in the University of Michigan’s Python for Everybody Specialization to learn how to program and analyze data with Python in just two months. To learn the basics of machine learning, meanwhile, consider enrolling in Stanford and DeepLearning.AI’s Machine Learning Specialization. A recent report from Gartner shows that the strongest demand for skilled professionals specialized in AI isn’t from the IT department, but from other business units within a company or organization. This AI evolution translates to a higher job outlook for AI and ML engineers.
- The six months of applied learning include over 25 real-world projects with integrated labs and capstone projects in three domains that will validate your skills and prepare you for any challenges you must tackle.
- Salaries for artificial intelligence engineers are typically well above $100,000 — with some positions even topping $400,000 — and in most cases, employers are looking for master’s degree-educated candidates.
- Once your area of interest is narrowed a bit more, prioritize learning the specific tools or technology required.
- Networking is also crucial in this field, and AI engineers may attend conferences, workshops, and AI-related events to stay updated with the latest advancements and research in the AI community.
AI Engineers mainly include analysis, algorithm development, programming , and integration of AI solutions into various applicationa and systems. In this way, AI attempts to mimic biological intelligence to allow the software application or system to act with varying degrees of autonomy, thereby reducing manual human intervention for a wide range of functions. In these placements, you’ll gain invaluable training in developing, deploying and maintaining AI systems under more experienced mentors. For mid-career transitions, highlight any related analytics or software engineering experience—volunteer for AI initiatives within your current organization.
Technical Skills & Concepts
Falling under the categories of Computer and Information Research Scientist, prompt engineer trainings have a median salary of $136,620, according to the US Bureau of Labor Statistics (BLS) [4]. The course AI for Everyone breaks down artificial intelligence to be accessible for those who might not need to understand the technical side of AI. If you want a crash course in the fundamentals, this class can help you understand key concepts and spot opportunities to apply AI in your organization.
Similarly, AI engineers play a vital role in the healthcare and biotech industries, working on medical imaging analysis, drug discovery, and personalized medicine. Throughout the program, you will build a portfolio of projects demonstrating your mastery of course topics. The hands-on projects will give you a practical working knowledge of Machine Learning libraries and Deep Learning frameworks such as SciPy, ScikitLearn, Keras, PyTorch, and Tensorflow.
The demand for skilled AI talent intensifies as groups and organizations race to combine AI solutions. The variety of AI task postings on Indeed.com grew by 485% from 2015 to 2021. In the latest industry survey, ninety per cent of groups said recruiting AI experts turned into a pressing or essential priority. Their work plays a pivotal role in harnessing the power of AI to revolutionize how technology interacts with the world and enhances the capabilities of computer systems to perform tasks that were once exclusive to human intelligence. Learn how to provide business insights from big data using machine learning and deep learning techniques.
Tariq Haque works as an AI engineer at CVS Health, where he helps the company make more informed decisions about their customers and interact with them more efficiently. Learners are advised to conduct additional research to ensure that courses and other credentials pursued meet their personal, professional, and financial goals.
Annual salary and job outlook
They are skilled in programming languages like Python or R, and they use frameworks such as TensorFlow, PyTorch, or Keras to build and train machine learning models. Through hands-on projects, you’ll gain essential data science skills scaling machine learning algorithms on big data using Apache Spark. You’ll build, train, and deploy different types of deep architectures, including convolutional neural networks, recurrent networks, and autoencoders.
