This research explores how a new relation of production—specifically, the shift from human managers to algorithmic managers on digital platforms—manufactures workplace consent. While most research argues the task standardization and surveillance that accompanies algorithmic management will give rise to the quintessential “bad job” (Kalleberg, 2000), I find that, surprisingly, many workers report liking and finding choice while working under algorithmic management. Drawing on a seven-year qualitative study of the largest sector in the gig economy, the ridehailing industry, I describe how workers navigate being managed by an algorithm. I begin by showing how algorithms segment the work at multiple sites of human-algorithm interactions and that this configuration of the work process allows for more frequent and narrow choice. I find individuals use two sets of tactics. In engagement tactics, individuals generally follow the algorithmic nudges and do not try to get around the system, while in deviance tactics individuals manipulate their input into the algorithm. While the behaviors associated with these tactics are practical opposites, they both elicit consent, or active, enthusiastic participation to align one’s efforts with managerial interests, and workers seeing themselves as skillful agents. However, this choice-based consent can mask the more structurally problematic elements of the work, contributing to the growing popularity of what I call the “good bad” job.