Small background: I have a degree in non-comp sci stream, but have been working as a dev/lead startups/corporates for last 10 years. Currently, I am in one of the big 4s as a SSE, but do not have any background in ML. Tech background would mostly be JVM...
So, how do I get started? Languages, technologies, books, projects, anything would help.
Python is pretty much the lingua franca of machine learning, so expect to use that, and I would recommend Keras as a framework for getting started with deep learning; it uses TensorFlow (or Theano) under the hood. scikit-learn it the main non-DL python ML library. You will almost certainly want to use Jupyter as an interactive Python environment.
Things like WEKA/deeplearning4j exist for the JVM, and they may be necessary for work, but are not where I would recommend starting.
If you're not aware of Kaggle, it's an ML competition website which hosts datasets, but also publishes descriptions of winning entries, though you'll find that deep learning is not what wins everything.
I would also suggest looking at some of the academic papers from conferences like ICML/NIPS/ICLR or just uploaded to Arxiv (though figuring out which ones are interesting will be harder to start); many papers are surprisingly approachable and knowing what mathematical topics are mentioned in cutting edge papers can help guide your learning.
This is mostly ML if you would like to dive into deep learning I think fast.ai is the best course for anyone with programming experience and you can also use the deeplearning.net Tutorial as a side reference. If you have a practical experience and would love to understand the theory behinds it then Deep Learning Book is the Bible.