Stanford professor and startup cofounder reveals how to land a job at an AI company: 5 insider tips for students

The artificial intelligence job market is often portrayed as a realm dominated by elite degrees and high-profile CVs. But according to Jure Leskovec, a Stanford University computer science professor and cofounder of an AI startup, Kumo, real-world skills matter far more than credentials.

In a recent interview with Business Insider, Leskovec shared insights on what actually gets candidates hired in AI.“If you want to work in AI, you need to show that you can actually do the work,” he said. His advice is straightforward: build meaningful projects, work with public datasets, post your work online, and deploy practical demonstrations.

Why these tips matter for students

Landing a role in AI is no longer just about where you studied or which degree you hold.

The industry moves rapidly, and recruiters increasingly prioritise demonstrated skills, problem-solving ability, and adaptability. Here are 5 actionable ways students can stand out in this competitive field.Build real projects and showcase themLeskovec emphasises that successful applicants demonstrate their abilities through tangible work. Hackathons, for instance, are a fertile ground for students to display initiative and teamwork within tight timelines. “They are a fantastic way to demonstrate initiative and teamwork in a short time. Even if you fail, you are showing that you are curious and proactive,” he told Business Insider.

At Kumo, a recent hire stood out not because of a prestigious degree but because they built a generative AI tool capable of analysing customer purchase data.

The takeaway is clear: problem-solving ability often outweighs the reputation of the institution on a candidate’s resume.Prioritise curiosity over credentialsFor Leskovec, adaptability is more important than a static skill set. “AI is evolving at a pace that surprises even those of us who work in the field every day,” he said in the interview.The most promising candidates are those who teach themselves new frameworks such as PyTorch and JAX, explore large language model tooling, and remain aware of emerging areas.

While top universities may secure interviews, it is curiosity, initiative, and flexibility that ultimately determine hiring decisions.“There is no playbook for AI. We are writing it right now,” he said. “I always value it when my students bring me solutions that have not been tried before, even if they are wrong.”Focus on thinking, not just textbook answersKumo evaluates applicants through multiple rounds of interviews that emphasise reasoning and problem-solving over rote knowledge.

Candidates are assessed on their thought process as much as their final answers.“Thinking outside the box may sound simple, but it is more critical now than ever,” Leskovec told Business Insider. He encourages aspiring professionals to question assumptions, experiment with unfamiliar methods, and consider multiple solutions to a single challenge. These habits, he explained, separate innovators from followers.Demonstrate collaboration and communication skillsTechnical skills alone are insufficient in modern AI workplaces. Leskovec seeks individuals who can communicate clearly, work effectively in teams, and consider the ethical and social implications of their work.“Your idea today could become the standard tomorrow, but it has to be built with people in mind,” he explained. Awareness of bias, empathy, and teamwork are essential components of a candidate’s profile, complementing technical expertise.Stay engaged with emerging AI trendsBeyond immediate coding skills, Leskovec emphasises continuous learning and engagement with the evolving AI landscape. Students and professionals who explore new methods, stay updated on research, and experiment with practical applications demonstrate readiness for real-world AI challenges.

A perspective grounded in experience

Jure Leskovec is a Slovenian-American computer scientist recognised for his pioneering work in large-scale network analysis and graph machine learning.

At Stanford, he teaches one of the university’s most popular machine learning courses and has co-founded several companies, including Kumo, which applies graph-based AI for enterprise data solutions. His insights highlight a central principle for aspiring AI professionals: demonstrating capability, curiosity, and collaboration can outweigh even the most prestigious credentials.For students aiming to enter the AI field, the message is consistent and practical: engage with real projects, embrace curiosity, and focus on both human and technical skills. Success, according to Leskovec, comes to those willing to think, experiment, and persist in an environment that is evolving faster than any textbook can keep up with.