Despite great strides in characterizing autism spectrum disorder (ASD) in early childhood, ASD research has largely overlooked the role socioeconomic status (SES) plays in early development. Broadly, SES captures the degree to which individuals are better or worse off in terms of their access to material and social resources (often measured via income and educational attainment). It remains unknown to what extent SES may be associated with the neural correlates of emerging language skills, above and beyond the known developmental vulnerabilities associated with ASD alone. This project was conducted using data collected through the SDSU Toddler MRI Project, which included behavioral and MRI data from 15- to 64-month-old children with autism and their typically developing (TD) peers (NASD = 39, NTD = 37). SES predictor variables included family-level (parental education, income-to-needs ratio) and population-level SES factors (neighborhood advantage index). Neural outcome measures included anatomical features (cortical thickness, surface area, and local gyrification) of canonical language regions, and functional connectivity between these regions (bilateral superior temporal gyrus—STG, posterior superior temporal sulcus—pSTS, inferior frontal gyrus—IFG, and middle temporal gyrus—MTG). Multiple linear regression models were used to test for associations between socioeconomic variables and neural indices, as well as SES x diagnosis (ASD vs. TD) interaction effects, controlling for covariates. FDR correction was used to control Type I error rate. Neighborhood advantage index (N-SES) was negatively associated with interhemispheric connectivity between several canonical language regions (partial r2 values = [0.07-0.10], all ps < 0.02), and with cortical surface area in the left and right IFG (partial r2 = 0.08 and 0.10, p < 0.02, respectively), in all children regardless of the diagnosis. Income-to-needs ratio (INR) was positively associated with local gyrification and cortical thickness in some of the same language regions (partial r2 values = [0.07-0.09], all ps < 0.03), in all children regardless of the diagnosis. This is the first study to report associations between SES variables and neural measures in young children with ASD, and serves as a starting point to better understand how SES becomes embedded in the brain early in life. Results from the present study demonstrate that SES variables account for variation in neural measures within the regions supporting language function in preschool children with and without ASD. These findings enhance our understanding of the effects of SES on brain development and are expected to contribute to developing improved prevention and intervention programs and policies aimed at reducing these effects.