Using R-UDF to make predictions on data based on a trained model

I am using Vertica to make statistical prediction based on machine learning models and I have a question concerning how to give the model to the UDF function as an argument.

Let's enter into detail: 

I have the following functions (simplified):

predict <- function (TrainData) {

# Load model from disc with load()
# Make predictions

}

predictFactory <- function(){

list(name=predict,udxtype = c('scalar'),...)

}

As you see, I am using the function as a scalar UDF but I have to load the model every time the function is called and that is time-consuming. I wonder whether it is possible to load the model only once and to give to the predict function as an argument. Something like this:

predict <- function (TrainData,Model) {

# Make predictions

}

predictFactory <- function(){

Model <- load(model)
list(name=predict,udxtype = c('scalar'),parameters = Model)

}

Is there any way of giving arguments to the predict function from the predictFactory function?

Thank you very much.