Ask HN: Should I invest in learning DL/ML mid- or late-career?

#1

Post by throwaway923857 » Wed, Mar 17, 2021, 7:16 PM UTC

I’ve been a software engineer generalist with a Frontend specialization for almost 20 years. During that time I’ve worked at companies large and small. Most recently I was at Google. I have a BSc in Computer Science from Canada.

After taking a year off mid-career I am considering spending an additional 6 months to learn machine learning before returning to work. I am attracted to ML because I like math and I’m excited by the promise of ML. I also want to shake things up and distinguish myself from other job candidates.

Is it worth the investment to learn ML at this stage in my career? Would 6 months be enough? What would my day-to-day look like: would I actually get to work on choosing and tuning models?

If you are actually working in a ML role or related I would appreciate hearing from you. Thanks!

Re: Ask HN: Should I invest in learning DL/ML mid- or late-career?

#2

Post by rawtxapp » Wed, Mar 17, 2021, 7:33 PM UTC

Are you interested in working with data and solving optimization problems? Are you ok with fairly repetitive processes (data cleaning, very similar models with minor tweaks here and there, etc)?

The application of ML is nowhere near as glamorous as it seems (having done ML at FAANG).

That said, it's still a great tool to have and a great thing to understand, who knows maybe you'll end up really liking the process and the data aspect of it. You won't become an expert at it in 6 months, but you can develop a relatively good understanding of it and build a couple practical projects and know what you don't know (essentially what are the different fields within ML, what kind of applications are there, what kind of models would you use in which kind of scenarios, etc).

I highly recommend learning it if you have time. Lots of good information on here and in /r/cscareerquestions and /r/machinelearning as well.

Re: Ask HN: Should I invest in learning DL/ML mid- or late-career?

#3

Post by throwaway923857 » Thu, Mar 18, 2021, 3:41 PM UTC

rawtxapp wrote: post #2

Are you interested in working with data and solving optimization problems? Are you ok with fairly repetitive processes (data cleaning, very similar models with minor tweaks here and there, etc)? The application of ML is nowhere near as glamorous as it seems (having done ML at FAANG). That said, it's still a great tool to have and a great thing to understand, who knows maybe you'll end up really liking the process and…

Thanks for your thoughtful reply.

I am concerned I won't like the grunt work of repetitive tasks like data clean-up and making minor tweaks to models.

Perhaps one day ML will do its own grunt work. If that happens I wonder what the role of ML engineers will be.