The AI explosion has made machine learning jobs hot commodities. But do you really need a Ph.D. to get one?

• Companies are hiring machine learning engineers as they seek to grow their AI talent pools.
• While some say the role requires a Ph.D., others say it doesn't need an advanced degree.

Companies are vying to hire the best machine learning engineers — some for salaries well over six figures — as they scramble to staff up as the AI sector booms. Many of these jobs ask for the applicant to have a Ph.D.

But earlier this week, members of the tech community pushed back on X, formerly Twitter, about whether an advanced computer science degree is really necessary for landing a coveted machine learning role.

"I don't wanna get a Ph.D. but wanna work as a Machine Learning Engineer," an X user wrote, kicking off a debate. "Dilemma of the Century."

In perhaps good news for the original poster, many who replied don't see not holding a doctorate as a barrier to entry.

In fact, Cristian Garcia, a machine learning engineer who works at Google's DeepMind AI division, wrote on X (in a post that was later deleted) that "A Ph.D. is an overkill or even red flag for an ML Engineer Role (IMO)."

Garcia, who says he doesn't have a college degree and is self-taught in machine learning, told Business Insider that Ph.D. programs don't always teach DevOps, data cleaning, data engineering, and skills related to backend work that are typically required to do the job.

"Knowing machine learning alone is far from enough," Garcia told BI. "In other words, the actual job is related to ML only tangentially."

A different X user, who claims to have a Ph.D. in computer vision, wrote that recruiters who see "Ph.D." in a job applicant's résumé might think the candidate lacks industry experience — and that they're too expensive and theoretical.

One respondent said a doctorate is only relevant for research, not machine learning engineering. Another even suggested that companies that list a Ph.D. as a hard requirement are most likely looking for researchers instead — "or don't know what they're looking for."

But not all techies think an advanced degree is unnecessary. An X user who claims to be a grad student in computer science said Ph.D. students can bring an innovative approach to real-world problems, which could be an asset to their employers.

The discussion comes as employers and would-be workers assess which skills and education are most useful as the AI job market booms. Recruiters at tech companies big and small have said that job applicants applying for AI-related roles don't necessarily need advanced STEM degrees to be hired.

Chris Foltz, the chief talent officer at IBM, previously told BI that when hiring for AI roles, the tech giant focuses on "prioritizing skills and experiences" over "traditional degrees" if candidates can demonstrate their AI knowledge.

Similarly, Nvidia's vice president of global recruiting Lindsey Duran said that applicants from non-traditional backgrounds can stand out if they can clearly emphasize their career milestones, leadership capabilities, and the impact of their past projects.

Alex Shapiro, the chief people officer at Jasper AI, an AI startup, even said that employees with less conventional backgrounds may, at times, be more attractive to hire than those with technical degrees.

One X user's response to the original post pointed out that a Ph.D. is just one way to become a machine learning engineer. And one other suggests, "Try at a startup, they'll take the risk" on someone without a Ph.D.. Then "break into a good company with that experience under your belt."