When you think of artificial intelligence (AI), what comes to mind? Maybe it’s a dystopian movie or TV show you love to binge watch where robots take over (Westworld, anyone?). Maybe it’s the sound of an automated spam call. Or maybe you’re up with the trends and immediately think of tools like ChatGPT.
All those answers are technically correct—AI spans a variety of mediums and industries, and it’s heavily integrated into and influenced by society today. Because of this, it’s a field with a lot of career potential.
“Within the last year, we’ve seen an absolute explosion in demand,” Aaron Sines, the director of talent, artificial intelligence and machine learning, at technical recruiting company Razoroo, told The Muse. “There’s a lot of disruption, there’s a lot of change, and things are moving at very high velocity,” he added. “But for those who are willing to lean in and embrace this new technology, there’s so much opportunity.”
Read on to learn what jobs are available in AI, and how to break into this exciting field.
What is AI?
Sines ties the emergence of AI to the Turing test, invented by mathematician and computer scientist Alan Turing in 1950—years before the term “artificial intelligence” came about in academic circles—that poses the question of whether a machine can perform just as well, or better, than a human in certain scenarios. Since then, the field has expanded to encompass many entities, which Sines broke down into four main categories:
- Machine learning: Machine learning is devoted to developing algorithms that allow machines to learn from data to make predictions or take action without explicit programming.
- Deep learning: Deep learning is a part of machine learning that teaches computers to process and recognize complex data and patterns.
- Natural language processing: Natural language processing enables machines to understand, interpret, and generate human language, and encompasses tools such as chatbots, translators, or virtual assistants.
- Computer vision: Computer vision is about developing algorithms and models that allow machines to interpret information from images, videos, or object detection, and plays a part in autonomous vehicles and facial recognition software.
Other subsets of AI, Sines noted, include robotics and AI ethics.
Why should you work in AI?
Sines argued there are several benefits to working in AI compared to other industries, specifically for people with a background in or passion for computer science, statistics, math, engineering, or technology:
- High demand: Because AI is a fairly new and rapidly growing field, there are a lot of job openings—800+ just on The Muse!—and fewer people competing for those jobs. This provides job seekers with ample choices between companies and roles, as well as salaries, work arrangements, and opportunities for upward mobility.
- Exposure to experts: Some of the best and brightest minds work in and are drawn to AI, Sines said. If working alongside smart people with specialized skill sets is important to you, this field could provide a lot of great exposure and experience.
- Stability: AI isn’t going anywhere anytime soon, and Sines noted that it comes with a lot of stability if you’re looking at the world 20 years out. “That's the best way to future-proof your career, is to be a part of the very threat itself,” he said.
- Impact: AI plays a role—and is becoming even more crucial—in many important industries, such as healthcare and energy, making it an attractive option for job seekers focused on purpose and impact in their careers.
All that said, Sines added, a lot of the perks in AI jobs vary depending on the size and culture of the company—at some organizations, for example, you might be required to work at all hours of the day, while at others there may be a more traditional or flexible schedule.
Tips for landing a job in AI
Here’s what you should consider before exploring and applying for jobs in AI:
Look beyond Big Tech
Major tech companies are some of the biggest recruiters of AI talent, but Sines said you can find AI roles sprouting up in other unexpected sectors, including agriculture, banking, retail, energy, and pharmaceuticals.
Get good at key programming languages
While there are some soft skills that are beneficial for breaking into AI (more on that below), realistically, your technical skills are what count the most to hiring managers. Python, TensorFlow, and PyTorch are the programming languages Sines said he sees on almost every resume he reviews for AI jobs.
To develop and hone these skills, you could sign up for a coding bootcamp or certification. If you’re making a bigger career change, you might want to consider going back to school or enrolling in a longer, more intense training program.
Be adaptable, a problem solver, and a good communicator and team player
Because the frameworks and tech used in AI are constantly changing, Sines said he often looks for candidates who are agile and willing to learn new things. The best way to showcase this, he added, is to come to the table prepared with stories of how you’ve overcome obstacles or adapted to new circumstances in previous roles.
Teamwork is also something he vets for: “You're working on really hard problems, and you have to be able to work as a team in order to solve those,” he said.
Join communities focused on AI
Sines noted that there are plenty of online forums and groups focused specifically on AI, and that’s where he looks when recruiting talent.
“If I'm trying to break into the space, I would definitely be living in those communities [and] engaging in those communities,” he said.
Collect examples of your work
Having a skill on your resume often isn’t enough. Sines said he looks for and regularly vets candidates’ portfolios to ensure they can practice what they preach.
“Being able to demonstrate projects they've been on, showcase the impact they made on those projects,” is important, he said. “We're really looking for a story around the success they've had.”
Building a strong online presence on platforms like LinkedIn can be a great way to do this, he added: “Optimize your profile, and we'll find you.”
Reach out to people in the space you admire
Networking is handy for landing just about any job, including one in AI. “A lot of these really focused AI divisions within enterprise companies often run like small companies,” Sines said—meaning employees on those teams may be easier to get in touch with than you think. So if there’s someone who’s doing exciting work you want to learn more about, don’t be afraid to shoot them a quick message on LinkedIn or over email asking for their advice or insights.
12 exciting jobs if you want to work in AI
If you’re sold on a career in AI, keep an eye out for these common roles. (Salary ranges are based on job descriptions provided on The Muse.)
1. AI engineer or developer
Pay range: $120,000 to $130,000
AI engineers simply design, develop, and implement AI systems. The category is so broad that it can span a variety of sectors and subsectors.
Find AI engineer jobs on The Muse
2. Machine learning engineer
Pay range: $142,000 to $283,000
Machine learning engineers, often part of a data science team, are mostly focused on developing machine-learning models and optimizing algorithms to make predictions, identify patterns, and improve processes.
Find machine learning engineer jobs on The Muse
3. Data scientist
Pay range: $76,000 to $245,000
Data scientists typically write code and use data visualization tools to extract insights from data sets to inform business decisions.
Find data scientist jobs on The Muse
4. Natural language processing engineer
Pay range: $150,000 to $250,000
Natural language processing (NLP) engineers fall in a niche within AI engineering focused on translating human language through computers, and are often involved in the development of tools like translation services and digital assistants.
Find natural language processing engineer jobs on The Muse
5. Computer vision engineer
Pay range: $84,000 to $126,000
Computer vision engineers, like NLP engineers, are a niche category of AI engineers who help computers analyze and interpret visual data from videos, images, and other mediums. It’s growing in the fields of medicine, agriculture, and transportation, among others.
Find computer vision engineer jobs on The Muse
6. AI ethicist
AI ethicists address the ethical considerations around AI and think about biases in AI systems. While more popular at big companies, he added, the role is becoming increasingly in demand as organizations realize the impact and risks of implementing AI.
7. AI researcher
Pay range: $161,000 to $374,000
AI researchers study AI and how the field is evolving. They’re often expected to publish in research journals or present to educational institutions, Sines said, to stay up to date on the technology in a way that benefits the organization.
Find AI researcher jobs on The Muse
8. Robotics engineer
Pay range: $165,000 to $175,000
Robotics engineers develop and build robotic systems and machines. While common in other fields, they play a role in the AI space, too.
Find robotics engineer jobs on The Muse
9. Machine learning operations engineer
Pay range: $159,000 to $325,00
MLOps engineers slightly differ from machine learning engineers in that they’re more focused on the operational aspects of building and managing machine learning models. In other words, they streamline processes so machine learning engineers can do their best work.
Find MLOps engineer jobs on The Muse
10. Automation engineer
Pay range: $86,000 to $200,000
Automation engineers conceive and develop technology specifically for fields such as energy, warehousing, manufacturing, and mining to improve and streamline production.
Find automation engineer jobs on The Muse
11. AI consultant
AI consultants, much like AI researchers, stay up to date on the latest AI trends to inform business decisions, collect data and reporting, and create more efficient strategies. Major consulting firms, such as McKinsey and BCG, have divisions specifically focused on this field.
Find AI consultant jobs on The Muse
12. AI recruiter
If you already work in, or are fascinated by, recruiting, consider specializing in hiring for roles in artificial intelligence and directly helping companies develop their tech talent. Sines, for example, started out in recruiting more generally in the tech space before focusing his efforts in AI.