Ask HN: How to Build a Career as Machine Learning Engineer?
I am a software engineer, who is involved in building (backend) data products (from building ETL, data-warehousing, scaling DB, .. etc).
My question to those who work in big companies and applied research labs, do engineers need to have MSc/PhD in Artificial Intelligence/Data Science to grow in the company.
I am not a data scientist, I am interested more into enabling Machine Learning in production (https://www.oreilly.com/ideas/becoming-a-machine-learning-engineer).
What are you recommendations ? If you already know programming, you can learn the basics of ML in a month. TensorFlow, Keras, PyTorch, etc, makes it super simple to build deep networks and you don't need any advanced math. That's where I would start. Also see the Stanford ML courses: http://cs231n.stanford.edu/ I think I am able to develop end-to-end ML projects. However, my question was about building a career in this space, how to move from junior to senior, from senior to being an expert in the field.