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These days you’ll be hard-pressed to find someone who hasn’t interrogated Siri (or Alexa), enjoyed the movie Netflix suggested, or fallen victim to purchasing that additional item Amazon recommended—all of which are only possible due to artificial intelligence. AI has been a field of study as far back as the 1950s, but advances have skyrocketed in recent years. These days AI is everywhere and has increasingly become part of all of our everyday lives. Thanks to AI, once tedious tasks are now simple, single-click activities. And as technology becomes even more pervasive, it will only continue to impact our personal and professional lives.

From healthcare to education and everything in between, AI and related technology are also changing the nature of work across the globe. Gartner estimates AI will create 2.3 million new jobs in 2020 while eliminating 1.8 million positions. And according to a 2019 Dun & Bradstreet report, 40% of organizations are adding more jobs as a result of adopting AI, while only 8% are cutting jobs because of the new technology. 

Jobs in AI:

With AI only becoming more embedded in our society, it’s no surprise that job seekers are turning to AI-related fields like machine learning and data science for careers in tech. These days, it seems as though every company is hiring some sort of specialist with knowledge in the field, typically with salaries well over $100,000 a year.

In fact, there is actually a surplus of jobs. According to Indeed, a popular online job marketplace, posts related to artificial intelligence on the site grew almost 30% in the last year while searches from job hunters went down by almost 15%. That’s a market gap that employers desperately want to fill.

Does this lucrative field pique your interest? Take a look into three common roles in the artificial intelligence job market and learn about what they actually entail to see if it would be a good career fit for you.

Data scientist

Commonly, data scientists work to analyze complicated raw data using statistical analysis, often around some sort of business problem that the company is facing. Artificial intelligence comes in to play in the ways that data scientists employ machine learning tools and create algorithms to help them solve complex problems. Udacity’s own Data Scientist Nanodegree program is a great place to start building these skills.

What do data scientists actually do IRL? A data scientist would forecast how many pastries a coffee shop should make on a given day for an entire region in order to maximize profitability and minimize waste. They would also be identifying the right locations for new pastry shops.

Machine learning engineer

Working as a machine learning engineer means developing systems that function beyond simply executing a list of instructions. This process typically involves creating sets of training data to feed into a model so it learns to make predictions and perform tasks without specific direction from humans. 

In action, a machine learning engineer might create a model and train it with large datasets in order to suggest music to a listener that they might like (think Spotify and Pandora). And, as the number one most in-demand AI job according to Indeed, the average salary for a machine learning engineer is over $140,000 annually in some parts of the country. 

Sound up your alley? Udacity can help you on your way with the Intro to Machine Learning Nanodegree program if you’re a beginner. Or, get started with the Machine Learning Engineer Nanodegree if you already have some experience.

Deep learning engineer

Deep learning work centers around using neural networks to develop systems that can learn on their own, without humans telling them what to do. Learning that the systems can do ranges from supervised learning: feeding in inputs and expected outputs and letting the machine figure out how to get there, to unsupervised learning: letting the system find patterns in unlabeled data. Often this work is very complex, research-driven, and experimental. 

Examples of work for a deep learning engineer would be developing self-driving cars, facial recognition, and robotics.

Deep learning is driving advances in artificial intelligence that are changing our world. Check out Udacity’s Deep Learning Nanodegree program to start building the skills necessary for a career in deep learning.

How to get a job in AI

The biggest commonality that all of these jobs have is that they are looking to hire someone who is well-versed in AI. While some traditional universities offer degrees specializing in AI, it is far more common for people to be staffed in these roles who have degrees in broader fields, like computer science, and then got further higher education specializing in artificial intelligence. 

Fortunately, there’s a ton of resources available for people who want to learn. Udacity offers AI Nanodegree Programs from professionals in the field and even includes the certification at the end of the course. The best part is that it is all 100% remote-based teaching that can be done while still working a regular job. What better way is there to jump-start a career in artificial intelligence?

So what are you waiting for? Take your career to the next level by taking a look at our Nanodegree programs at our School of AI today.

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Jennifer Shalamanov
Jennifer Shalamanov
Jennifer is a content writer at Udacity with over 10 years of content creation and marketing communications experience in the tech, e-commerce and online learning spaces. When she’s not working to inform, engage and inspire readers, she’s probably drinking too many lattes and scouring fashion blogs.