How to create a Time Series Training Dataset with variable sequence length
I solved it the following way:


zero padding all time series that are smaller than the longest one
adding a Masking()layer with masking_value=0. which ignores all zero values before feeding the network. 


The part of the model with the Masking layer looks like the following:

model = keras.Sequential()
model.add(layers.Masking(mask_value=0., input_shape=(None, 1)))
model.add(layers.LSTM(100))


Additional Info: Implementing the Masking Layer for a Model with two separate Inputs was kind of unconvinient with a the Keras Functional API, therefore i implemented that part of the model with the Keras Sequential API and connected it to the rest of the model which is implemented with the Functional API.