  As Einstein's equations for binary compact object inspiral have only been
approximately or intermittently solved by analytic or numerical methods, the
models used to infer parameters of gravitational wave (GW) sources are subject
to waveform modeling uncertainty. Using a simple scenario, we illustrate these
differences, then introduce a very efficient technique to marginalize over
waveform uncertainties, relative to a pre-specified sequence of waveform
models. Being based on RIFT, a very efficient parameter inference engine, our
technique can directly account for any available models, including very
accurate but computationally costly waveforms. Our evidence and
likelihood-based method works robustly on a point-by-point basis, enabling
accurate marginalization for models with strongly disjoint posteriors while
simultaneously increasing the reusability and efficiency of our intermediate
calculations.
