Recruiters say these positions generally require a technical background and coding proficiency.
Candidates can also stand out with strong soft skills, side projects, and knowledge of AI ethics.
As the companies shift to focus on AI, workers are pivoting to get in on the hottest new job in the market.
Many of these "AI jobs" fall under the title of machine learning engineer, prompt engineer, data scientist, or AI researcher. But what do they actually entail?
Lisa Hufnell, head of talent at conversational AI company Rasa, told Business Insider that while the job category has become a sort of buzzword, these positions use a version of the same skillset required in other roles in the industry.
"It's such a small pool that have been doing it," Hufnell said about AI positions. "You have to look for those transferrable skills."
BI spoke to four companies that recruit for AI roles to get an idea of what the basic qualifications for these roles are — and how candidates can stand out.
Recruiters mentioned computer science, data science, mathematics and applied science as some of the main degrees they look for.
Andree Mendoza, a technical recruiter at talent firm Carex Consulting Group, said that coursework can be a great additive since AI is a "newer space." It's important to have a deep understanding of the LLM space and stay up to date with best security practices, he said — but it may not be enough to start out.
"To really break into the space, I'd say you really need a technical background," Mendoza said.
That's not to say that people who come from different schools of study or careers can't get a job in AI — but a background in one of these core areas seems to be the norm.
Coding proficiency
Hufnell said that getting into AI has less to do with AI-specific technologies and more about being a strong engineer in general. That means being proficient in programming languages.
Proficiency in Python or JavaScript is considered another must-have for applicants in the AI job space. VP of hiring at company RelationalAI Bria Porter also mentioned C++ and SQL as other programming languages that she looks for.
Despite concerns about AI taking over coding , Art Zeile, CEO of tech career marketplace DHI, assures that coding remains a valuable skill. He emphasizes the problem-solving, coding, and debugging abilities required for success and recommends a coding certification to enhance your job prospects.
Other ways to stand out
Hufnell said people at the front of the line have to consistently learn and adapt. While having a solid grasp of technologies is obviously crucial, candidates also need to demonstrate adaptability and strong soft skills.
"With engineering and AI, it's about finding individuals that are not only technically proficient, but they need to show they're agile learners too," Hufnell said.
This is usually demonstrated in the behavioral interview process, she said. But Hufnell also noted that something like a boot camp in AI ethics would stand out to her on a résumé.
Side projects can also serve as a differentiator , Zeile said, although it may not be necessary for all applicants. Zeile said recruiters are increasingly looking for people to demonstrate the skills they list on their resumes, whether that be through a 45-minute Python test or in an interview.
That can also mean using the tools in everyday situations. In addition to side projects, Porter said automation is another skill recruiters are looking out for to see that candidates can use AI to maximize their efficiency on the job.
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