Indian-origin former Meta executive shares 4 practical tips for breaking into AI: ‘Don’t assume you need a PhD’

Her career has crossed research labs, classrooms and industry roles. After teaching and working in various research positions, Parikh joined Facebook AI Research in 2016. For years, she split her schedule between Meta’s Menlo Park AI lab and teaching computer vision at Georgia Tech, before moving fully into Meta in 2021. She eventually became a senior director working on generative AI.

In 2024, she left to start Yutori with her husband and a longtime friend.

Looking back, Parikh said one of the biggest myths about the field is that only people with doctorates can meaningfully contribute. She believes practical exposure, whether through startups, large tech labs, open-source experimentation or online communities, can be just as valuable. “If you keep putting in the time and effort to whatever you’re doing, you’ll be able to stand out, and you’ll also have learned a bunch of skills along the way,” she said.

At Yutori, she added, the team prioritises hands-on experience, model training expertise and technical interview performance over degrees.

Importance of flexibility

Parikh also highlighted the importance of staying flexible in a field that shifts quickly. She recalled how some researchers hesitated to embrace deep learning a decade ago because they were tied too strongly to older methods or labels. Her own path moved from computer vision to multimodal AI and then to generative systems.

“If I’d held onto my identity as a computer vision researcher without exploring these other things, I would’ve missed out on opportunities,” she said.

For those entering the field, Parikh advised choosing projects and roles that spark genuine curiosity rather than chasing what seems strategically safe. She said many of her most fulfilling decisions, including leaving a stable senior position at Meta to launch a startup, came from following her interests rather than certainty.

She also stressed the value of finishing what you start. During the pandemic, Parikh created a YouTube series featuring open, personal conversations with AI researchers. “I thought seeing the human side of the AI researchers we put on a pedestal would show folks in the community they could have a similar level of impact,” she said.

The series boosted her visibility and reinforced a lesson she now shares widely: ideas only create opportunities when carried through. “If you haven’t seen something through to the end, it can’t have its impact or lead you to the next thing. If there’s something you’d like to do, just go do it, instead of overanalysing and not taking steps forward,” she said.