Has anyone been bait-and-switched when applying to machine learning positions?
I work on ML infrastructure at Microsoft. Mostly accelerating common ML libraries. I applied to AWS for an ML position but when talking to one of the engineers he told me that his team doesn't really do any machine learning work -- they are just given the model from a research team. He said he and the whole team want to do more ML work but in reality they are just taking the model and building a service around it. This seemed like a total bait-and-switch to me. I've read about how a lot of ML engineers spend most of their time doing data prep, but I hadn't heard of something like this.
Very common scenario
I do that as an ‘ML Engineer’
Very common. You’re part of a ML team but all you do is software engineering
I’ve been getting that a lot from Amazon & Google. They try to lure me in with a promise of ML; but then pair me with non ML or tangentially ML teams.
Because ML is a buzz word for recruiting. I regard recruiter emails about ML jobs as NEGATIVE signs. though I have done some applied ML work previously, I didn’t actively participate in this field in recent years. I don’t see why recruiter can easily discover my prior ML experience. So my conclusion is that’s a recruiting buzzword and I should avoid those jobs.
At Microsoft ML positions are mostly with Microsoft Research.
There are plenty that are not... but I don't want to reveal what team I'm on
Typical scenario across several large enterprises claiming to be ML leaders. But it's not so surprising to me because if you think about it, these companies really can't start investing in employing full-time "data scientists", at least not yet. Data Scientists are already overrated and so are "ML Engineers". Doesn't stop you from unpacking the R or Python algorithm for your own learning. So enjoy the ride for the next couple of years before the real data scientists take over the world.
What role are you applying to? If it's SDE then it's very expected that you build a scalable service on top of a given model, because you're an SDE. But if you're a research scientist it's purely ML (mostly). I'm an SDE and our sister team is a mix of SDE and research scientists (mostly scientists and just a couple of SDEs). We build production scalable services on top of what they model. Their SDEs are mostly a bridge between an engineer and a scientist. They don't build scalable services, but they build prototypes for the scientists' models and they understand the ML as well. You might be interested in such roles.
Messaged :)
Not exactly for ML, but I was hired as a Data Scientist but worked as a Data Engineer for my last job.
Could you please describe the ‘Data Engineer’ role that you have to do? Maybe you had to do both because there aren’t dedicated data engineers? From what I know it’s a step up for a Data scientist to move onto Data Engineering. Moreover, Data engineering + Data scientist will be a killer combination. Once you have amassed real good experience on both sides, try out AirBnB, FB, Netflix. So if you are getting the opportunity to do the real ‘Data Engineering’ work, don’t think of it as bait and switch. Instead it’s a blessing in disguise. Make the best of it.
4 years later, and Google kinda missed the mark here. DS's that take on DE work get pigeonholed into future DE positions.
It’s really common
It is, yes.
You've seen it at Google?