We consider the problem of training-based code-timing estimation for the asynchronous direct-sequence code-division multiple-access (DS-CDMA) system. We propose a modified large-sample maximum-likelihood (MLSML) estimator that can be used for the code-timing estimation for the DS-CDMA systems over the resolvable multipath channels in closed form. Simulation results show that MLSML can be used to provide a high correct acquisition probability and a high estimation accuracy. Simulation results also show that MLSML can have very good near-far resistant capability due to employing a data model similar to that for adaptive array processing where strong interferences can be suppressed.