This talk will introduce a new R package that has recently been released on CRAN. *serrsBayes* uses a sequential Monte Carlo (SMC) algorithm to separate an observed spectrum into a series of peaks plus a smoothly-varying baseline, corrupted by additive white noise. We have implemented this algorithm using RcppEigen and OpenMP to provide parallel, scalable performance for spectroscopic analysis. I will give a brief introduction to Raman spectroscopy and SMC, as well as discussing my experience with interfacing between R and C++.