Earlier quoted context omitted.
Limited budget demands that you, get creative and dig-deeper still. Could a local QA guy get the job done in a pinch? Will your Ops support someone working remotely, even off-shore? Economical solutions require some flexibility.
You're looking at this too rationally. That's not meant as snark. The people responsible for these requirements aren't acting rationally. They want Bill Gates, Microsoft CEO for the price of Bill Gates, Harvard Freshman. And if they can't find that person, they complain there's a shortage of good candidates.
Ask HN: Who are the engineers that don't get hired?
11–20 of 32 posts
Re: Ask HN: Who are the engineers that don't get hired?
#12Invest more in getting the right kinds of candidates.
Re: Ask HN: Who are the engineers that don't get hired?
#13This is interesting. I screen a lot of ML researchers and engineers. The process typically starts with a 30-90 minute phone screen (it ends faster if I don't like you). I start by discussing the company and the position, in as much depth as the candidate wants. Then we discuss one project of the candidate's in depth, both for some technical expertise but also to suss out what the candidate, as opposed to a team, actu…
1. Hire depending on your team. There are candidates who are amazing data scientists but do retarded shit like select * from table order by rand() on a ten billion row table and bring down the cluster. Sometimes, it is OK because your team has incredibly strong engineers who can work in close combinations with these people. Sometimes you can't really afford that. At my current workplace, my manager did a really good job of hiring people who are fullstack (data + backend + viz + ml) while having strong preferences in one direction or the other. So you might have an incredibly strong ML engineer who can roll his own ML code out on Spark, while also being open to writing back-end infrastructure code once in a while. Or you might have this guy who thinks in data pipelines all day long, but will spend a bit of time thinking about mathematical model. The teams work well.
2. Hiring for ML teams is really really hard. When I was in San Francisco at my previous job, we used to screen quite a few candidates everyweek. We would see failures similar to what you posted. Either engineers who knew fuck all about ML or people who were good at the theory but didn't know how to code. Somehow, at my current job in NYC, we lucked out because we have a bunch of really awesome people who moved out of finance but want to continue to live in NYC.
> They may (or may not) have a very deep understanding of one tiny piece, but lack a decent understanding of the breadth of the field.
This is close to what I have seen from both sides of the table. But, one thing that annoys me is the number of teams where people have pet algorithms that they are obsessed about. They keep asking questions about those pet algorithms and ding a candidate for not knowing that specific algorithm in depth. One should be able to be flexible while doing this.
> They don't know deeply at least one or two techniques and tools.
I think we see people from so many different walks of life that for junior people the goal is to make sure that they know the shit that they have in their resume and drill them if they don't. As in, we don't hire for specific techniques or tools because the team has its own collection of tools/libraries (Spark/Hadoop/Python/Word2Vec/CF etc) which you will be able to pick up fast if you are good enough.
Re: Ask HN: Who are the engineers that don't get hired?
#14Re: Ask HN: Who are the engineers that don't get hired?
#15Re: Ask HN: Who are the engineers that don't get hired?
#16Being on both sides, I feel interview processes are a part of the problem too. Every place I have interviewed assumes that the interviewers are good and by default, the candidate is bad. While it is probably statistically true, it makes things worse if a good candidate gets rejected because of an issue with the interviewer's own abilities.
Re: Ask HN: Who are the engineers that don't get hired?
#17Thing is, companies and jobs differ, and so do people. I've seen top performers from company A fail in the interviews at company B, and vice versa. Leaving both companies under the impression that the other company employs 'bad' developers.
Whether or not your skills+potential can be used optimally by a company depends on so much details, like cultural fit, to which extend you agree on their paradigms (methodology, problem solving ideas, prioritization, etc).
Long story short; companies are usually looking for the most optimal choice for their job openings, and so are applicants. This results a way more complex matching strategy that just 'could do the job'.
Perhaps John Nash can help us with optimizing these strategies. Until than, I think 1:50 to 1:99 ratio's are here to stay.
Re: Ask HN: Who are the engineers that don't get hired?
#18* As far as graduating seniors, when you post a job offer, you get maybe 10% of the resumes from people with either a CS/CE major or minor. That's not to say they can't code (in my experience a resume from a non-CS major with good experience is a much better bet than a resume from a CS major with little or poor experience). But we literally get people whose experience totals up to "took a 'How to write HTML' class once freshman year as an elective" applying to jobs involving low-level C
* Actual on-site interviews are very expensive; unless you are really hurting for people, you need a cheaper (and potentially less precise) way of weeding things out.
* With the exception of graduating seniors, there really are relatively few good candidates actively seeking work; most of the good ones have jobs (and you can hire them, but that usually isn't counted in the X% of resumes get offers, which usually refers to responses to a job posting; hiring people away from their current jobs usually starts in a different manner).
* On the other hand huge numbers of people who are desperate for work send in resumes. The less harmful of these are the ones who obviously are unqualified and clearly just spammed every job offer listed regardless of the requirements. Since we aren't talking about graduating seniors (see above) the majority of the not-obviously-unqualified often even have relevant work experience, but that's just because it takes time for people to fire you.
I am talking about people with 2-5 years of experience working in language X who are barely able to (or sometimes even completely unable to) write FizzBuzz in language X.
Another example was someone with over 5 years of OS kernel development, who in the interview was unable to describe what exactly they did in those 5 years and they didn't seem to know a much about any of the various OS topics we tried asking them about: scheduling, interrupts, DMA, filesystems, memory paging, IPC.
These people are particularly harmful, since there are very few tells at all on their resumes (and no reliable ones), you would have to interview all of them, which gets expensive. The majority can't get past a phone-interview, but when you are talking about
This leads to a lot of companies not even bothering to interview people (again ignoring those graduating from school) without referrals from current employees, or some other way of weeding out the massive numbers of "good resume, but bad candidate" submission that also will, as a side effect, weed out some of the "good resume, good candidate". It also means that if you are looking for work, and can't find it, then either you are unqualified, or need to get referrals from friends who have jobs at companies that are hiring.
Re: Ask HN: Who are the engineers that don't get hired?
#19This is interesting. I screen a lot of ML researchers and engineers. The process typically starts with a 30-90 minute phone screen (it ends faster if I don't like you). I start by discussing the company and the position, in as much depth as the candidate wants. Then we discuss one project of the candidate's in depth, both for some technical expertise but also to suss out what the candidate, as opposed to a team, actu…
This is very detailed. Pretty similar to what I have seen in industry. A few comments from a guy who has been involved in several ML teams for the past few years. 1. Hire depending on your team. There are candidates who are amazing data scientists but do retarded shit like select * from table order by rand() on a ten billion row table and bring down the cluster. Sometimes, it is OK because your team has incredibly st…
> I think we see people from so many different walks of life that for junior people the goal is to make sure that they know the shit that they have in their resume and drill them if they don't. As in, we don't hire for specific techniques or tools because the team has its own collection of tools/libraries (Spark/Hadoop/Python/Word2Vec/CF etc) which you will be able to pick up fast if you are good enough.
I think you misread what eshvk was saying; he isn't saying that they don't know one or two specific techniques or tools, but rather they don't have any tools/techniques at all that they know deeply. If you read what followed the part you quoted, it should become clear.
Re: Ask HN: Who are the engineers that don't get hired?
#20For me, it's difficult to hire an engineer that's not specifically interested in what my company is doing. A very common reason I've passed on engineers in the past is "they're okay... but they don't seem really excited about what we're doing here..."