Artificial intelligence (AI) is a branch of computer science that programs machines to think like humans. Simulating human behavior may sound like something out of a science fiction novel, but it’s a tool that allows you to rethink how you use, analyze, and integrate information to improve business decisions. AI has great potential in finance, national security, healthcare, criminal justice, and transportation.
According to PricewaterhouseCoopers Global Artificial Intelligence Survey [1]AI could contribute up to $15.7 trillion to the global economy by 2030, more than the current output of China and India combined. This projected growth means that organizations will turn to AI to enhance business decision-making and improve efficiency.
For AI engineers, that means plenty of growth potential and a healthy salary. Read on to learn more about what an AI engineer does and how to get started.
What is AI engineering?
AI engineers use AI and machine learning (ML) techniques to develop applications and systems that help organizations increase efficiency, reduce costs, increase profits, and make better business decisions.
AI engineering focuses on developing tools, systems, and processes that enable the application of artificial intelligence to the real world. Any application where a machine imitates human functions, such as problem solving or learning, can be considered artificial intelligence. Algorithms are “trained” by data, which helps them learn and improve performance.
While using Netflix, Spotify, or YouTube, you may have encountered the result of AI engineering where machine learning makes customized suggestions based on your behavior. Another popular example is transportation, where AI and machine learning technologies power self-driving cars. AI can help in healthcare by allowing robots to perform surgeries and generate automated diagnostic imaging.
Is AI for me?
The AI forEveryone course breaks down AI in a way that makes it accessible to people who don’t need to understand the technical aspects of AI. If you need a crash course in the fundamentals, this class will help you understand key concepts and find opportunities to apply AI to your organization.
Artificial Intelligence Engineer Responsibilities
AI engineers play a critical role in organizations using AI. They plan the AI strategy and define the problems that AI should solve. They are responsible for building and implementing AI development and production infrastructure. Here are some of the specific tasks and responsibilities of an AI engineer:
AI Engineer Salary and Job Outlook in India
AI engineering is a specialty with good job growth and tends to have high salaries.
The average base salary for an AI engineer in India is ₹9,000,000 [2].
The Economic Times reports on the promising employment outlook in the AI sector, predicting that India will add more than 2.3 million AI-related jobs by 2027. [3].
AI engineers typically work for companies like Google, IBM, and Meta, helping them improve their products, software, operations, and delivery. They may also work in government agencies or research facilities aimed at improving public services.
How to become an AI engineer
Becoming an AI engineer requires basic computer, information technology (IT), and math skills, which are essential for directing AI programs. Here’s how to get started with AI engineering.
1. Learn the necessary skills in the AI engineer course.
You will need to build technical skills, including knowledge of the tools that AI engineers typically use.
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programming: You may want to learn a programming language such as Python, R, Java, or C++ so you can build and implement models.
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Probability, statistics, and linear algebra: AI engineers need these skills to implement various AI and ML models.
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Big data technology: AI engineers work with large amounts of data, so they typically need knowledge of Apache Spark, Hadoop, and MongoDB to manage it all.
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Algorithms and frameworks: You need to understand ML algorithms such as linear regression and naive Bayes, and deep learning algorithms such as recurrent neural networks and generative adversarial networks. It must also be able to be implemented using a framework. Popular AI frameworks include Theano, TensorFlow, Caffe, Keras, and PyTorch.
Learn these skills through online courses and boot camps to help you launch your AI career.
Do I need a degree to become an AI engineer?
You don’t necessarily need a degree to become an AI engineer. More and more people are turning to professional certification programs to learn the skills they need and prepare for interviews.
AI engineers typically have a bachelor’s or bachelor of science degree in computer science, engineering, or information technology. Jobs in the AI field are highly competitive, but if you can prove that you have a strong skill set and do well in interviews, you can start your career as an AI engineer.
2. Apply for a job.
Applying for a job with little or no experience can be intimidating, but it may be helpful to know that jobs that don’t require experience are filled every day. There are many ways to enhance your resume for success in your job search. For AI engineering jobs, you may want to highlight specific projects you worked on in your work or classes that demonstrate your broad understanding of AI engineering.
If you apply for a job, you will probably be asked for an interview. Don’t be discouraged if you apply to dozens of jobs and don’t hear back. Data science is a high-demand (and high-paying) career field, and companies can receive hundreds of applications for a single job.
Preparing for an interview requires practice and preparation, especially for technical roles in AI engineering. You’ll want to hone your interviewing skills to show hiring managers that you’re the best fit for the job. You need to explain why you are developing, deploying, and scaling a particular algorithm. These interviews can be very technical, so make sure you can prove how you solved the problem and why you chose to solve it that way.
3. Gain work experience.
Even entry-level positions and internships may involve multiple interviews. But once you find a job, it’s time to prove yourself and learn as much as possible. You can then apply the skills you learn to provide business insights and solutions that can change people’s lives, including healthcare, entertainment, transportation, and consumer product manufacturing.
Explore Artificial Intelligence on Coursera
Start your career as an AI engineer with IBM’s AI Engineering Professional Certificate. Learn how to generate business insights from big data using ML techniques, and gain critical skills to deploy algorithms with Apache Spark and models and neural networks with Keras, PyTorch, and TensorFlow. Start today and study 10 hours a day and you’ll be done in 4 months.
