  Near-field radio holography is a common method for measuring and aligning
mirror surfaces for millimeter and sub-millimeter telescopes. In instruments
with more than a single mirror, degeneracies arise in the holography
measurement, requiring multiple measurements and new fitting methods. We
present HoloSim-ML, a Python code for beam simulation and analysis of radio
holography data from complex optical systems. This code uses machine learning
to efficiently determine the position of hundreds of mirror adjusters on
multiple mirrors with few micron accuracy. We apply this approach to the
example of the Simons Observatory 6m telescope.
