Correcting log-bias in the output of an XGB
From this perspective, modern ML regression techniques are not different to classic ones. A mean unbiased model on the log scale will automatically be mean biased after retransformation (by Jensen's inequality). 

Depending on the aim of your analysis, applying some retransformation bias correction factor might be useful as well for algorithms like XGBoost. (Be careful with models that impose L1/L2 penalties on the intercept though - a rare occasion.) 

The specific correction factor can be calculated directly from the residuals in the same way as for OLS.