In theory, the gig economy facilitates flexible, digitally mediated employment arrangements. Why do some people wind up doing gig work while others do not? We focus on how online participation inequalities, and Internet use experiences and skills, shape the composition of online gig workers. Specifically, we analyze a unique survey data set from a national sample of 1512 U.S. adults that includes information about background attributes and behaviors, detailed measures of Internet experiences and skills, as well as questions about whether study participants had completed specific steps necessary to becoming a task worker on two prominent gig economy platforms: Amazon Mechanical Turk and TaskRabbit. We use Bayesian regression to compare four stages of gig economy participation. Workers who participate in the gig economy tend to be younger, more highly educated, and more skilled Internet users. This implies that the gig economy increases labor market stratification and that digital participation inequalities compound labor inequalities.