Submitted by diffusion-xgb t3_ysc7gs in MachineLearning
farmingvillein t1_iw0pgz2 wrote
Reply to comment by Peantoo in [D] Current Job Market in ML by diffusion-xgb
> but not having CI/CD and cloud experience is basically gatekeeping me
Big tech doesn't really care about this. Are you passing leetcode & ML skills screens? This is where I would focus.
(Well, would have, prior to the current crash...)
Peantoo t1_iw0wukj wrote
Eh, I've had 3 interviews so far and that's what they want. I've got lots of experience with data wrangling, model development, etc, but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."
I'm signed up for a lot of training courses, specifically GCS and AWS, so maybe I'll have more luck once I've completed them. There's still the issue of getting practical experience, but I'll figure it out at some point.
farmingvillein t1_iw0yjja wrote
> but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."
That doesn't sound like big tech?--Meta, Alphabet, etc. heavily use their own internal tools.
> but I keep hitting that wall of, "we use AWS and need someone to help with the production side of things."
Also doesn't sound like "truly" ML roles.
Peantoo t1_iw0zxg9 wrote
Not really aiming at big tech. I guess I should have clarified that, my mistake. If you know MLOps, you know stuff like Apache Spark, Databricks, etc are part of the ML pipeline. I agree, it isn't very ML, but that's what they keep asking for.
farmingvillein t1_iw1av5m wrote
Yes, understood--you're aiming at the wrong market, is what I was trying to get at.
Peantoo t1_iw1lcvt wrote
I guess I'm just not sure where my market is. This job was literally called "Machine Learning Engineer," and their description had all the things I was looking for. Not sure if it was a bait and switch or if I need to be looking for certain terms or job titles.
farmingvillein t1_iw1vkd1 wrote
Sounds like you are looking more for a role advertised with more of an R&D role--"data scientist", "ML research engineer", etc.
Role names are fluid/arbitrary, but "ML Engineer" at anywhere other than the largest shops (or very AI-specialized startups) is generally going to be someone who can help get an ML system into production (hence the cloud concerns).
Your general options (other than somehow boning up on cloud and passing the interviews now) would be to more narrowly tailor the roles you apply for (per above); continue to apply for MLE but be aware of the issues (per above); and/or apply to some general SWE roles so that you can get some more modern commercial/cloud stack experience.
As a general statement, 1-2 years of a generic SWE role would probably do wonders for your infrastructure-level knowledge; i.e., you'll probably be able to write your own ticket after this.
That said, if you have zero interest in expanding into this, I'd just focus on applying roles that are more narrowly written.
Peantoo t1_iw2uic8 wrote
That's some good advice. I'm more interested in doing similar work in a green tech field, so I guess I'll focus more on the SWE skills. I don't necessarily want to limit the scope of what I apply to just yet. I'm sure if I poke around and pretend like I can't do my job otherwise, I can get some funding allocated to an IRAD project just for me. Should be able to swing a "mock cloud infrastructure for future ML/AI development." Plus, it'll probably help them out in the long run. The gov is both incredibly long and short sighted sometimes. "We want AI, it's the future, we want to invest in it for the next two decades" along with "wait, you need computers to do AI?"
I'm not excited about staying where I am for that long, but that whole "write your own ticket" part might be worth the time.
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