As companies shift their focus to AI, workers are pivoting to get into the hottest new jobs on the market.
Many of these “AI jobs” fall into job titles such as machine learning engineer, prompt engineer, data scientist, AI researcher, etc. But what exactly are they?
Lisa Hafnell, head of talent at conversational AI company Rasa, told Business Insider that while the role has become something of a buzzword, these positions require the same skill sets as other roles in the industry.
“There are very few AI jobs out there,” Hafnell said. “You have to look for transferable skills.”
BI spoke to four companies hiring for AI-related roles to find out what the basic qualifications for these jobs are and how candidates can stand out.
Related Fields of Education
Recruiters in this field cite technical education as one of the key priorities when hiring talent for AI roles.
Recruiters cite computer science, data science, mathematics, and applied science as the top degrees they are looking for.
Andree Mendoza, a tech recruiter at staffing firm Carex Consulting Group, said that because AI is an “emerging field,” the coursework could be a big added value. Having a deep understanding of the LLM field and staying up to date on security best practices is important, but that alone might not be enough to get started, he said.
“I think you really need a technical background to really get into this field,” Mendoza said.
This is not to say that people from different academic backgrounds or professions cannot get AI-related jobs, but experience in one of these core fields seems to be the norm.
Coding Ability
Hafnell said that to get into the AI industry, it's more important to be a good engineer in general, rather than AI-specific skills — that is, to be fluent in a programming language.
Proficiency in Python or JavaScript is also a must for AI job applicants, and Bria Porter, vice president of recruiting at RelationalAI, also lists C++ and SQL as desirable programming languages.
Despite concerns that AI will replace coding, Art Zeile, CEO of tech careers marketplace DHI, is adamant that it remains a valuable skill. He emphasizes the ability to problem-solve, code, and debug needed to be successful, and encourages people to get coding certifications to improve their employability.
Other ways to stand out
Hafnell said frontline talent needs to continually learn and adapt: While a strong understanding of technology is obviously important, candidates also need to demonstrate adaptability and good soft skills.
“In engineering and AI, it's important to find people who are not only technically proficient, but also have the ability to learn quickly,” Hafnell said.
This is typically demonstrated during the behavioral interview process, Hafnell said, but he also noted that something like an AI ethics bootcamp would stand out on a resume.
Side projects can also be a differentiator, but they're not required for all applicants, said Zaile, who said recruiters are increasingly looking for candidates who can demonstrate the skills they list on their resume in a 45-minute Python test or interview.
That might mean using the tools in everyday situations. In addition to side projects, automation is another skill recruiters are looking at to see if candidates can use AI to maximize efficiency in their jobs, Porter said.
