Your Salary Benchmarks Are a Year Old — And It's Costing You Candidates

Your salary benchmarks might be 12 months out of date. And in a market where AI hiring drove ML engineer salaries up 15% in under a year, that gap can cost you a top candidate before Friday's offer even goes out. In this episode, we dig into how Pave has flipped the compensation benchmarking model upside down — replacing the annual survey cycle with continuously updated data from over 8,700 companies and more than a million employee records. We cover what PaveOS can actually do for your merit cycles, the AI features worth paying attention to, and the honest trade-offs if your workforce sits outside tech. If you run total rewards at a tech company or growing startup, Pave is worth understanding. And if you've ever had a candidate decline because your offer was based on last year's data, this one's for you.