We present a pipeline based on a random forest classifier for the identification of high column density clouds of neutral hydrogen (i.e. the Lyman limit systems, LLSs) in absorption within large spectroscopic surveys of z>~3 quasars. We test the performance of this method on mock quasar spectra that reproduce the expected data quality of the Dark Energy Spectroscopic Instrument and the WHT (William Herschel Telescope) Enhanced Area Velocity Explorer surveys, finding >~90 per cent completeness and purity for N_HI_>~10^17.2^cm^-2^ LLSs against quasars of g<23mag at z~3.5-3.7. After training and applying our method on 10000 quasar spectra at z~3.5-4.0 from the Sloan Digital Sky Survey (Data Release 16), we identify ~6600 LLSs with N_HI_>~10^17.5^cm^-2^ between z~3.1 and 4.0 with a completeness and purity of >~90 per cent for the classification of LLSs. Using this sample, we measure a number of LLSs per unit redshift of l(z)=2.32+/-0.08 at z=[3.3,3.6]. We also present results on the performance of random forest for the measurement of the LLS redshifts and HI column densities, and for the identification of broad absorption line quasars.