This paper models the assimilation process of migrants and shows evidence of the complementarity between their destination experience and upon-arrival human capital. Bayesian learning and dynamics of matching are modeled and empirically assessed, using panel data of wages from the Bangkok labor market in Thailand. The analysis incorporates (1) the heterogeneity of technologies and products, characteristic of urban labor markets, (2) imperfect information on migrants' types and skill demanded in the markets, and (3) migrants' optimal learning over time. Returns to destination experience emerge endogenously. Estimation results, which control migrants' selectivity by first-differencing procedures, show that (1) schooling returns are lower for migrants than for natives, (2) the accumulation of destination experience raises wages for migrants, (3) the experience effect is greater for more-educated agents, i.e., education and experience are complementary, and (4) the complementarity increases as destination experience accumulates. The results imply that more-educated migrants have higher learning efficiency and can perform tasks of greater complexity, ultimately yielding higher wage growth in the destination market. Simulations show that, due to the complementarity, wages for different levels of upon-arrival human capital diverge in the migrants' assimilation process.