Nvidia Chief Software Architect Jonathan Ross has suggested that job applicants may improve their chances of getting shortlisted if they use the same artificial intelligence models that recruiters use to screen resumes. Speaking at the Sohn Investment Conference 2026, as reported by Business Insider, Ross noted that research indicates AI hiring systems may favor resumes generated by their own underlying large language models (LLMs). His comments come amid increasing reliance on AI tools to review applications and automate parts of the hiring process, raising fresh concerns about bias and fairness in AI-based recruitment systems.
AI Prefers Its Own Kind
Ross, who previously helped develop Google's TPU chip, stated, "AI likes to use AI" while discussing automated hiring systems. He referenced a study showing that "resumes generated from one LLM are preferred by that same LLM over the resumes from the other." During a conversation with Infinitum CIO John Yetimoglu, Ross explained that recruiters now use LLMs to determine who to interview, but applicants need to figure out which LLM the recruiter is using.
Strategic Resume Crafting
Ross suggested that applicants may need multiple AI-generated versions of their resumes to improve their chances of passing automated screening systems. "So, you should build one resume with Claude or Opus 4.7 and one with ChatGPT, and you'll have the highest probability of being selected, basically," he said. This approach, according to Ross, could significantly boost a candidate's chances in an increasingly AI-driven hiring landscape.
Research Backing the Claim
As reported by Business Insider, Ross appeared to reference a late-2025 academic paper titled "AI Self-preferencing in Algorithmic Hiring." The study tested more than 2,200 resumes across 24 job categories. According to the findings, applicants using the same AI model as the evaluator were between 23% and 60% more likely to be shortlisted compared to candidates using human-written resumes with similar qualifications. This statistical advantage highlights the growing influence of AI in recruitment and the potential for bias in automated systems.
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