I study optimal income taxation when human capital investment is imperfectly observable by employers. In my model, Bayesian employer inference about worker productivity drives a wedge between the private and social returns to human capital investment by compressing the wage distribution. The resulting positive externality from worker investment implies lower optimal marginal tax rates, all else being equal. To quantify the significance of this externality for optimal taxation, I calibrate the model to match empirical moments from the United States, including new evidence on how the speed of employer learning about new labor market entrants varies over the worker productivity distribution. Taking into account the spillover from human capital investment introduced by employer inference reduces optimal marginal tax rates by 13 percentage points at around 100,000 dollars of income, with little change in the tails of the income distribution. The welfare gain from this adjustment is equivalent to raising every worker’s consumption by one percent.