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HomeBlogData ScienceWhat are the Roles and Responsibilities of an Artificial Intelligence Engineer?
Today, over 77% of devices use some form of AI, whether to switch on lights, reply to text messages, or for complex tasks like detecting anomalies or analyzing user behavior. On its way to becoming the ‘new normal,’ AI is poised to have a ubiquitous presence in our daily lives.
I know that it takes many masterminds to design and develop these applications. However, I can give you an insight into my part as an AI engineer in the process. Primarily, I help develop AI-powered tools and applications. This requires proficiency in developing software, working with data, and programming. That being said, I did not initially start as an AI engineer. To get this position, I enrolled in a comprehensive AI certification to land a role as an AI engineer.
So, let me help you with my experience and knowledge of an AI engineer’s roles and responsibilities. This article will discuss all the skills required to become an AI engineer.
AI is the science of simulating human intelligence by using machines, software, and networks of complex algorithms to carry out specific tasks. These could range from reading, comprehending, generating code, detecting gunshots, and alerting authorities to being a stock broker, predicting the weather, and creating art. It's safe to say that AI can take on anything.
This is done by developing programs that train on existing data to learn and perform like humans.
AI engineers are responsible for developing, programming, and training complex algorithms that can mimic human intelligence while carrying out specific tasks. As AI is a vast domain, an AI engineer must be familiar with multiple processes, including, but not limited to, software development, data science & engineering, programming, and testing.
Their work aligns with that of a data engineer because AI is a data-heavy science, i.e., it requires massive volumes of data to train on. While AI engineers are expected to be experts at coding and programming, they are often not required to work on code pertaining to data-related operations (mining, annotation, cleaning, etc). Instead, their work begins once this data is extracted and ready to be used in creating and testing machine learning models and APIs.
Let’s explore the roles and responsibilities of AI engineers at different levels of experience and expertise.
Entry-level AI engineers are required to assist in AI application development by overseeing fundamental parts of the process. While the exact AI engineer responsibilities depend on where you work and what you work on, some fundamental ones include
Average Salary: An entry-level AI engineer makes over $117,377 (Source: Springboard) annually.
AI engineers with over three years of experience are expected to partake in more responsibilities throughout the AI application development process. Besides the fundamental roles of an AI engineer, they are responsible for
Average Salary: An AI engineer at a mid-to-senior level earns $138,506/year (Source: Springboard) on average.
Senior artificial intelligence roles and responsibilities cover the entire AI-powered SDLC (software development life cycle). During the process, they’re responsible for:
Please note that all the above-mentioned duties are in addition to an AI engineer's fundamental roles and responsibilities, i.e., programming applications, managing data and databases, evaluating models, etc.
Average Salary: A senior AI engineer earns $159,000 on average. However, it may go as high as $203,000 with proficient skills.
To become proficient, your AI engineer roles and responsibilities require you to have a diverse set of skills, including both hard and soft skills.
Some hard skills you must have as an AI engineer:
Joining an Artificial Intelligence Bootcamp can give you a better understanding of all the hard skills you must hone to become a proficient AI engineer.
Employers also consider your cultural fitness and soft skills as an AI engineer to ensure you’re a good fit for their organization. These skills include:
Before applying for an AI engineer’s role, you must investigate jobs in artificial intelligence. The most prominent AI job roles include principal scientist, AI engineer, machine learning engineer, computer vision engineer, data scientist, statistician, etc. Let’s look at the typical job requirements for all AI-based roles.
As mentioned in the section above, AI engineers must thoroughly understand AI and ML algorithms and models, know programming languages like Python, LISP, Scala, etc., and be familiar with different AI security vulnerabilities.
They must also be team team-player, be able to communicate complex information precisely, think critically, and manage deliverables within tight deadlines.
Having some experience in leveraging AI strategies to real-world problems and building AI models can add a feather to your cap. But if you are only starting out as an AI engineer, you can also use some additional certifications or projects as a testament to your knowledge and skills. Maintaining a portfolio of projects you work on is another way to keep track of your work.
AI is a vast and developing field, with hundreds of advancements and roles coming up. As per predictions, AI’s economic impact could be staggering, reaching up to $15.7 trillion by 2030! These numbers are only proof of the limitless potential that artificial intelligence holds! If you’re interested in AI technology and want to pursue a career, this is the time to explore more and start gaining professional knowledge and experience. Enrolling in certifications is an excellent way to do this; you can check out KnowledgeHut’s AI certification to get a head start.
The exact utility depends on the application and industry where AI is being used. However, AI has many benefits, like reducing human error, providing digital assistance, making unbiased decisions, automating repetitive tasks, finding new innovations, scaling operations, providing 24x7 functionality, and many others.
AI is expected to continue taking center stage in several industries and sectors. More tech adoption is expected in MSMEs (micro, small, and medium enterprises), with salaries catching pace with bigger players. Consequently, AI engineers can expect more opportunities across several industries. More jobs will also open up in cybersecurity, cloud computing, IT servicing, and automated sales and marketing.
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