The radiation pattern within quark-and gluon-initiated jets (jet substructure) is used extensively as a precision probe of the strong force as well as for optimizing event generators for nearly all tasks in high energy particle and nuclear physics. A detailed study of modern jet substructure observables, jet angularities, in electron-proton collisions is presented using data recorded using the H1 detector at HERA. The measurement is unbinned and multi-dimensional, using machine learning to correct for detector effects. Training these networks was enabled by the use of a large number of GPUs in the Perlmutter supercomputer at Berkeley Lab. The particle jets are reconstructed in the laboratory frame, using the 𝑘 T jet clustering algorithm. Results are reported at high transverse momentum transfer 𝑄 2 > 150 GeV 2 , and inelasticity 0.2 < 𝑦 < 0.7. The analysis is also performed in sub-regions of 𝑄 2 , thus probing scale dependencies of the substructure variables. The data are compared with a variety of predictions and point towards possible improvements of such models.