Some of the most common you could mention include:
max_depth - This is the maximum depth per tree. This adds complexity but at the benefit of boosting performance.
learning_rate - This determines step size at each iteration. A lower learning rate slows computation, but increases the chance of reaching a model closer to theoptimum.
n_estimators - This refers to the number of trees in an ensemble, or the number of boosting rounds.
subsample - This is the fraction of observations to be sampled for each tree.