131–140 of 215 posts
I work for a non-tech company as a solo full stack dev. I have been able to interview with fortune 500 companies and get offers. I have been getting contacted by recruiters from hot startups, Microsoft, Google, AWS, Amazon and Meta. I am not sure if I'm stupid but I really don't know how "no experience" can be better than wrong experience. There is always things you learn, better negotiation tactics, your value to a…
I work for a non-tech company as a solo full stack dev. I have been able to interview with fortune 500 companies and get offers. I have been getting contacted by recruiters from hot startups, Microsoft, Google, AWS, Amazon and Meta. I am not sure if I'm stupid but I really don't know how "no experience" can be better than wrong experience. There is always things you learn, better negotiation tactics, your value to a…
What I have learned is this also means they don't want someone who will disrupt or question the status quo.
In infosec for example, I work or worked at a place with a lot of really smart people but they have been at the same company long and the idea of doing things in a layered defense strategy (not perimeter/firewall/ids centric) way is "the wrong way" to them even though that is best practice now. On the other end I keep running into people that have worked at startups like uber for a long time and their answer to threats is "use only macs" or "get everyone a yubikey". No shit? Lol
You can't be experienced and not have some bad experience but managers and people in power disregarding experienced people's opinion's without applying critical thinking is laziness and incompetence.
You need experienced people as well as people with little experience but who are motivated to learn on any good team. It's like a sports team lineup, you don't want everyone having the same skill and experience you want them to have what is right for the position they are playing.
Earlier quoted context omitted.
I think they probably mean "ML engineering" as in training pre-existing models in jupyter notebooks, the new "data science". The people that actually create/engineer anything new and useful in ML is <1% of people that "work in ML".
Are those positions real? It feels like once the model didn't work if you did not have the background to know why it wasn't working then you'd be in trouble real quick.
And "understanding how to use the models effectively" is being generous for what gets a lot of these people in the door.
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> Stats? The average age at google is 29 years old. Which means half of their company is YOUNGER than that No, that’s not what that means.
True! It doesn't "mean" that. But you get the picture.
I generally enjoy Dan Luu’s advice, but IMO it’s best approached with the understanding that his professional and social network is somewhat of a bubble that doesn’t reflect the average person. Specifically, he cites a statistic that 50% of the people with “no experience” he knows are getting ML and other such jobs at Big Tech companies. In this case, I think he’s likely pre-filtering his sample set to people with si…
As a hiring manager, I've found entry level roles to be the hardest to fill well. No metric is a guarantee of a quality candidate. I loathe whiteboard programming, but for entry level jobs it's at least a signal that they're putting in the work to figure out how to be successful within a structure. Beyond that, I want a narrative for the candidate's career...both where they've been and where they want to go. It helps…
I’d love to have a candidate who tells me “I love creating products”. I’ve hired a 100% junior, no school (formerly teacher), he kicks ass, I’ve increased his salary by 10% every 2 months since 8 months. He just loves the art of creating a product, maintaining it in prod, interviewing customers… You are correct, it’s incredibly hard to detect.
Great on you for rewarding him generously for his performance!
This shows the distinction between the value of resumes (whether it’s school or job or whether) is in large part just signaling and not actually about skill set.
Relevant comment of mine from a previous, mostly unrelated thread (context was "Berkeley gives you a parking space if you work there and win a Nobel"): > The rich get richer. I remember filling out school and early job applications. I was struck by how my list of awards and recognitions was kind of a sham—most of them were each a consequence of some earlier achievement, and so on. It felt like getting a check and bei…
Parking space? In the old days they built Seaborg a stairway up to LBL, so I heard.
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> he cites a statistic that 50%... Not a statistic so much as an anecdote. He makes it pretty explicit, I thought.
Eh, even if it’s an anecdote, it comes off as actionable advice: “make sure you apply to Google/Amazon/Facebook as your safety jobs, since you’ve got a 50% chance of getting in there anyway.” Which feels… optimistic.
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How should they know where they want to go if they're entry-level? They haven't seen what the future paths are really like. This leads to a mentality of "the only safe entry-level candidate is one with five years' experience doing exactly what we do," and I saw that in how one of the places I worked did their hiring. It led to much lower-quality entry-level candidates than if the company had accepted some risk and ta…
> How should they know where they want to go if they're entry-level? I think it’s totally reasonable to expect people to have a plan. It’s also totally reasonable, and expected really, for that plan to change over time. But working without a plan, which implies working without goals, is rarely a recipe for success.
though im nearly 20 years into my career i barely can predict where i'll be in one year, let alone five
for the first 10 years my only goal was to make more money and not hate work
not a great goal from a hiring manager perspective
as a hiring manager, i ask what folks like to do and see if that aligns with what we need them to do
This was also true in the military: At basic training, our drill instructors often said that recruits with no experience shooting weapons were easier to train than other recruits who had experience because it was much easier to teach best practices to someone who was a "blank slate" than it was to retrain best practices to someone who learned improper methods. I haven't exactly seen this idea like-for-like in the "co…
This is a good analogy but inadequate. What Dan is saying goes beyond that. In the scenario you're describing, it is rational to prefer those recruits—for exactly those reasons. The behavior that Dan describes involves a heap of irrationality. Dan's piece that he linked (about "Mike") really is important to understand the thing that he's referring to. http://danluu.com/programmer-moneyball/ > (Kudos on being able to…
I've found this comment section to be a bit shocking, to be honest. I thought a message like "Trendy hiring managers will discriminate against you if you work for Walgreens or a bank or use a Microsoft stack, compared to if you have no professional experience" would be simple enough to be successfully transmitted to readers.