I started my career in machine learning with absolutely no knowledge in it. It is definitely some thing that you can learn on the job. You do need a background in linear algebra/ statistics to understand the theory behind different algorithms that will help you decide what algorithm to choose (SVM vs Random Forest for ex.).

Like suggested in the other comment, the best place to start is probably by working on projects with open data sets. Try experimenting with different algorithms, feature engineering techniques. This is especially important because there are plenty of algorithms and identifying which algorithm works for which kind of data set is useful.