- work often spans broad business departments, involves genuinely interesting engineering trade-off problems between accuracy, scale, budget, and interpretability
Some of the cons:
- You have to be wary to avoid companies in which machine learning is just a name for data engineering / devops / business analytics, or where it is hype or aspiration and no substance
- No matter what your job will mostly be the unsexy stuff to get a system working. Only maybe 10-20% is going to be the actual model development or experimental side
- Companies not yet well versed in machine learning can have huge sticker shock at what a competitive compensation package is like, and waste a lot of your time on interviews and end up way off the mark on compensation.
- good pay
- exciting time to be alive
- work often spans broad business departments, involves genuinely interesting engineering trade-off problems between accuracy, scale, budget, and interpretability
Some of the cons:
- You have to be wary to avoid companies in which machine learning is just a name for data engineering / devops / business analytics, or where it is hype or aspiration and no substance
- No matter what your job will mostly be the unsexy stuff to get a system working. Only maybe 10-20% is going to be the actual model development or experimental side
- Companies not yet well versed in machine learning can have huge sticker shock at what a competitive compensation package is like, and waste a lot of your time on interviews and end up way off the mark on compensation.