A growing number of American workers earn income through platforms in the gig economy which provide access to flexible work (e.g. Uber, Lyft, TaskRabbit). This major labor market innovation presents individuals with a new set of income smoothing opportunities when faced with unemployment shocks. I use US administrative tax records to measure take up of gig employment after unemployment and to evaluate the effect of working in the gig economy on workers' overall labor supply, skill acquisition, and earnings trajectory. To do so, I utilize variation in the introduction of gig platforms across counties over time, interacted with variation in individual-level predicted propensities for gig work based on pre-unemployment characteristics. In the short run, I show an increase in gig work following an unemployment shock and that individuals are correspondingly better able to smooth the drop in income that they experience. However, individuals stay in these positions and are less likely to return wage jobs. Thus, several years later, their earnings lag significantly behind comparable individuals who did not have gig work available. Among older workers this can be a long-term improvement as an increase in gig work corresponds to a beneficial postponement of social security benefits and a reduction in new applications for social security disability income (SSDI) that follow unemployment shocks.