Geographic frictions constrain the efficiency of labor markets by limiting the access of firms to workers outside their local commuting zones. Work-from-home (WFH) arrangements have the potential to alleviate these frictions by expanding the effective reach of job vacancies. Using population-level data from Sweden that link vacancy postings, employer-employee matched registry data, and data on job search behavior, I examine how signaling WFH in job ads reshapes firms’ labor market access. To determine WFH positions, I implement a generative AI–based text classification to identify WFH vacancies, distinguishing between hybrid and fully remote jobs. To explore geographic and quality effects, I leverage job seekers’ search behavior to construct new measures of revealed commuting preferences, based on the location of in-person applications, and of applicant quality, based on the firm quality of their other applications. These approaches provide new tools for measuring non-wage amenities and labor market access using search behavior. I find that WFH vacancies attract significantly more applicants, particularly from geographically distant job seekers, with effects strongest for non-urban workplaces which face thinner local labor markets. While average applicant quality declines slightly, WFH vacancies attract stronger candidates at the top of the distribution, especially when the WFH signal is salient and informative. These results suggest that offering WFH can reduce geographic mismatch primarily by connecting isolated firms to a larger and higher-quality applicant pool.