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This dead-simple roadmap will help you navigate the AI landscape (so you never feel lost or overwhelmed again). It’s called the AI Pathway Compass — here’s how it works:

In the rapidly evolving world of artificial intelligence, navigating the career landscape can be as complex as the algorithms themselves. But what if there was a straightforward, easy-to-follow roadmap that could guide you through the maze of AI career opportunities?

Author

Adrian Mohnacs
November 15, 2023

Introducing the AI Pathway Compass — a uniquely designed framework that demystifies the journey towards a successful career in AI. Whether you’re a fresh graduate, a seasoned tech professional, or somewhere in between, the AI Pathway Compass is tailored to help you identify and pursue the AI role that best suits your skills and aspirations.

In this article, we’ll delve into how this roadmap works, breaking down each step to ensure you never feel lost or overwhelmed in your pursuit of a fulfilling career in AI.

Data Scientist

Let’s bust this myth about AI!

All these fancy words like neural nets and deep learning is just a small part of what makes up the AI you use everyday. Data is the real source of intelligence. Large amounts of data are given to AI algorithms, patterns are found, and capabilities emerge.

And data scientists are the ones who wrangle the massive amount of data being stored online so AI models can use them. These professionals have many paths beneath the title of “data scientist”. With each being a specialist in their own way.

For those more mathematically inclined study data science. Where you crunch numbers to present to business. Or go with data engineering if you like coding. Preparing data formats for model training.

AI Engineer

Unpopular opinion: an AI engineer is not as great as you think. It requires a pretty significant number of skills and specializations you probably don’t have.

The work will be hard and you will have to learn a lot more just to stay competitive. But why?

AI engineering is more than just algorithms, frameworks, and tools. Engineering is grounded in solving problems. In understanding how technology can be used to create meaningful solutions.

Most people get this wrong when they only focus on the code.

But let’s say you got this part right. You know what to build and how it can help. AI engineers mainly focus on bringing existing models to production and maintaining benchmarks.

Nothing innovative worth publishing on Arxiv about.

AI Researcher

The reason you are using AI on a daily basis without even knowing is because of the superheroes behind the scenes. AI researchers.

With access to unlimited amounts of computer and the entirety of the data stored on the internet at their fingettips, this specialized group is responsible for creating AI that has never been seen before.

AI researchers spend a large amount of their time in the “academic context” meaning they are reading papers, coding prototypes, and attending conferences. Once sure they have something unique to provide the industry these researchers partner with AI engineers to bring the model to production.

Large corporations are those most likely to hire for position similar to AI researcher because they have the budget.