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I was expecting something along the lines of how AI/ML was considered a sexy career path, but there are very few jobs available and high competition for those j
by SCUSKU 4y ago
I was expecting something along the lines of how AI/ML was considered a sexy career path, but there are very few jobs available and high competition for those jobs. So, as a result, you end up with the only available jobs as data engineering/ML ops/backend that supports ML teams. I am happy for this author and their success, but they clearly are not representative of the majority of the people in the ML job market.
- PartiallyTyped 4y agoI think I have a decent CV, with quite a bit of experience for a master's student. I have been searching for a job in MLE, for a bit now with very little to show for it, as I am either getting no responses, or responses claiming that they are looking for more experienced people, and particularly those that had experience with a particular stack. In all honesty, after 6 years of studying, with 4 of those years studying ML, to be told that I lack experience with some particular stack as the ~~excuse~~ reason for rejection feels like a slap in the face. And all that ignoring everything that expects 3+ years experience for entry level positions.
- benibela 4y agoThat is why I am doing a Post Doc
- hebrox 4y agoMay I ask what you're working on?
- benibela 4y agoOn causality There is this interpretation of Bayesian networks that the parents are the true causes of a node and to predict what happens if you change a variable you need to remove the edges from the parents to that variable from the network. And then I study what you can do with that method
- dunefox 4y agoI have been in a similar position with NLP - either you already have a lot of experience (maybe even a PhD) or you're a mathematician or statistician. Otherwise you're left out.
- PartiallyTyped 4y agoFunny enough, my experience is NLP and DeepRL.
- dunefox 4y agoYour best chance might be to apply at small companies. They often have data and want to take advantage of it but haven't so far. Of course they're not doing any research or are Google, Amazon, etc. but hey.
- deleted 4y ago[deleted]
- mellavora 4y agowhere are you located?
- PartiallyTyped 4y agoEurope. I am open to relocating pretty much anywhere in Western Europe or Scandinavia so my horizons are pretty open.
- captaincaveman 4y agoSo central or eastern Europe ... yeah, thats gonna be tough!
- PartiallyTyped 4y agoNo, actually in Scandinavia.
- NalNezumi 4y agoAs a fellow Scandinavian I was in a similar position as you 2018, except that I was looking for MLE job with a (Software) Robotics background.(because beside ABB there were no robotics interest there). Tl;dr I moved to Japan and worked in ML (ish) job. Once you start working it becomes remarkably easier to not be scoffed for lack of experience (even if you learned very little in that job) Job security is high in Scandinavian countries and as an consequence people hire very risk-averse. risky/not so established jobs such as ML positions, they'll be actively looking for reasons NOT to hire you
- nbardy 4y agoStart building projects on your own with the most common tooling. Having something to show cuts down barriers.
- mola 4y agoI suspect they are looking for experienced ppl because they don't have one and don't exactly know how to manage ML and what to do with it and hope someone else will come and show them.
- htrp 4y agoYou have to be doing something wrong or applying for the wrong types of jobs (lots of MLE jobs are just glorified dba jobs at certain job companies).
- deleted 4y ago[deleted]
- rdedev 4y agoReading comments like this is a bummer. I am currently doing my masters with a focus on NLP. At this point I'll be pretty happy to get a job even if it just boils down to only deploying ML models. Even for such a role of companies expect years of experience or a PhD I don't know how I can even get a job in the first place
- visarga 4y agoI sometimes interview candidates for ML engineering roles, and let me tell you most of them have trouble with basic concepts. It's great when I find someone fluent, for a change.
- PartiallyTyped 4y agoBasic concepts referring to what precisely?
- 21723 4y agoAll these fields have that problem. There are people who are great at aping the signals (and even beating publication metrics) but really don't know anything. When they show up on a job, they get put into a PM (or actual management) role to limit the damage they can do. They learn enough lingo to be able to convince 90% of people they know what they're talking about (congrats on being in that other 10%, though) and will move up forever. Meanwhile, people who actually know their shit are usually too busy actually being smart to play the games necessary to get themselves hired in a hyper-competitive job market. So it goes.
- orzig 4y agoI can only speak for Boston area, but I've been on teams who regularly welcome those with only 1-2 years of experience (even if it wasn't that relevant, as long as they had relevant schooling). I don't know if you consider that positive or negative evidence, but there it is.
- georgeburdell 4y agoThat was my pre-conception as well. I know some people who have tried to switch from other engineering to ML/AI, some taking as much as a year off work, and the only successful ones already had a network in the Bay Area from their previous associations (prestigious university/employer).
- rakejake 4y agoYep, at that level, there is a ton of competition. The self-driving industry is almost like the video game industry and actually has a ton of employees who previously worked in video games. They are definitely much better compensated in ADAS but the work culture is similar (anecdotally so YMMV). ML is the sexy wing of the tech industry, so it tends to attract the people who are willing to put in the hours (for interviews as well as towards work).
- 21723 4y agoThis is because there isn't really much demand for genuinely innovative ML in the tech world. It's a third-circle nice-to-have, not part of the core business. It enables the business to say they invest in R&D (tax writeoffs, marketing) and it also makes it easier to hire the grunts who'll do the scut work, thinking they'll one day be working on something more interesting (which they won't be). Competition for bullshit "data science" jobs isn't that tight. For genuine research that actually matters, it is, and that's because most of these positions exist as recruiting tools (you're getting paid to let the company say you work there) and that's always going to be a thin ledge to try to perch on.
- qumpis 4y agoThe OP actually started his career as a ML engineer (or SWE even) and transitioned into research without a PhD. Can you elaborate on your "which they won't be" comment?
- rakejake 4y agoThe fact that it is possible to jump from MLE to a research role in Deep Learning means that this pathway is accessible to anyone who is a decent SWE and has some math skills. But there are much fewer research positions. So there is an element of luck and being at the right place at the right time. Today, the competition for research positions in a "sexy" STEM field (think quantum computing, black holes, DL, RL) is quite high. DL just happens to be a field where it is possible to get into research without investing too much time while also making a lot of money, so this is a dream job for many.