Objective A 2010 survey identified disparities in salaries by gender and underrepresented minorities (URM). With an increase in the emergency medicine (EM) workforce since, we aimed to 1) describe the current status of academic EM workforce by gender, race, and rank and 2) evaluate if disparities still exist in salary or rank by gender. Methods Information on demographics, rank, clinical commitment, and base and total annual salary for full‐time faculty members in US academic emergency departments were collected in 2015 via the Academy of Administrators in Academic Emergency Medicine (AAAEM) Salary Survey. Multiple linear regression was used to compare salary by gender while controlling for confounders. Results Response rate was 47%(47/101), yielding data on 1,371 full‐time faculty: 33% women, 78% white, 4% black, 5% Asian, 3% Asian Indian, 4% other, and 7% unknown race. Comparing white race to nonwhite, 62% versus 69% were instructor/assistant, 23% versus 20% were associate, and 15% versus 10% were full professors. Comparing women to men, 74% versus 59% were instructor/assistant, 19% versus 24% were associate, and 7% versus 17% were full professors. Of 113 chair/vice‐chair positions, only 15% were women, and 18% were nonwhite. Women were more often fellowship trained (37% vs. 31%), less often core faculty (59% vs. 64%), with fewer administrative roles (47% vs. 57%; all p< 0.05) but worked similar clinical hours (mean±SD= 1,069±371 hours vs. 1,051±393 hours). Mean overall salary was 278,631(SD± 68,003). The mean (±SD) salary of women was 19,418(± 3,736) less than men (p< 0.001), even after adjusting for race, region, rank, years of experience, clinical hours, core faculty status, administrative roles, board certification, and fellowship training. Conclusions In 2015, disparities in salary and rank persist among full‐time US academic EM faculty. There were gender and URM disparities in rank and leadership positions. Women earned less than men regardless of rank, clinical hours, or training. Future efforts should focus on evaluating salary data by race and developing systemwide practices to eliminate disparities.