DATA SCIENCE · AI DESK
Most hiring platforms say they use AI to match candidates. I write about what's actually happening under the hood — the ranking systems, the retrieval logic, and why the results are usually worse than they should be.
Areas of Expertise
About Pranav
“Pranav spent most of his career on the engineering side. Building things, breaking things, figuring out why a model that looked great in testing was quietly failing in production. He got into writing because he kept reading coverage of AI hiring tools that didn't match anything he recognized from actually working on them.
He's done research in ML optimization and retrieval systems. His honest take is that most of what gets called AI in hiring is a search problem with better branding. He writes about the gap between what these systems claim to do and what they're actually doing — the ranking logic, the matching criteria, the parts that don't get mentioned on the product page.
At Joblet.ai he covers candidate matching, search relevance, and hiring platform infrastructure. He's particularly interested in why job search results are still so bad given how much money has gone into trying to fix them.
Credentials & Experience
From the Desk
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Weekly Newsletter
One short, technical email. Recent papers worth reading, model evals from production, and how to know when an AI feature is actually helping the user.
