6 ms·

How would start ups compete well with those salaries?

dsacco 9y ago
They can’t, and don’t. The secret is that experienced PhDs (mostly) dominate the high end of “AI” hiring, but don’t have much title or departmental differentiation from people who are “only” specialized software engineers in top tech companies. But this isn’t very well known, large companies want to recruit as much talent as they can regardless of role, and startups want to compete on paper - therefore, you have the following effects: 1. Startups give whatever sexy title they want to the people they can afford, which makes titles fairly useless, because they almost never can afford the talent commanding “sky-high” salaries. 2. Within large tech companies like Google and Facebook, it’s hard to immediately tell which of the many data sciencey, machine learning-y titles correspond to the truly stratospheric salaries versus the engineers that work with those roles. For some teams, like DeepMind, Google Brain or FAIR, it’s easier to tell. But for others it’s a mixed bag. For comparison, see the fashionable term of art “quant” in the financial industry, which has similarly devolved into marketing and a bimodal distribution. As a rule of thumb, you generally can’t trust AI titles or salaries at startups unless those startups are really known for their talent; further, you can safely assume that, at companies capable of paying for top talent, the very impressive salaries belong to titles which seem the most exotic and out of reach for general engineers in the job description. Fortunately startups don’t really need to compete for top talent as a genuine technological differentiator, they just need to engage in signaling, so this is mostly a non-problem. Startups almost never have problems usefully improved by the cutting edge of machine learning research, and can instead use off the shelf tools and existing software to accomplish the same things. Frankly, it’s exceptionally rare for a startup to even have the massive data, pipeline and munging infrastructure requisite for actual research.
- pm90 9y ago
  This actually makes a lot of sense. I have a lot of friends employed as Data Scientist or Data Engineers who don't seem to be able to explain exactly what they do, or describe what "research" they are doing. From what I understand, it seems like they are designing pipelines that ingest data, run an off the shelf AI algorithm and display nice graphs. There is a lot of pipelines you can design for different kinds of data so I imagine they always have something to do.
- salmonfamine 9y ago
  Is this not the impetus behind the "data engineer" title that's been thrown around lately?
- mr_toad 9y ago
  It’s not just startups. Big business and government have slapped the ‘data scientist’ label on anyone who can drum up a chart in Excel. As Napoleon said: titles don’t honour men, men honour titles.
svantana 9y ago
In my experience, the best scientists are not motivated by money, at least not beyond enough to provide a comfortable lifestyle. For me it's much more important to work on interesting problems in a good team. Also, startups can provide an exhilarating feeling of 'anything is possible' which you rarely get at a large corporation.
Spooky23 9y ago
You don't. You sell solutions. In most enterprises, 90% of problems can be solved by somebody who can get phone calls answered, a $20/hour intern and Excel.
- sgt101 9y ago
  I think that's a sign of enterprise dysfunction - problems that can be solved in that way aren't real problems, they are neglect and delinquency.
  - Spooky23 9y ago
    At some level, sure. But... Consider the wide variety of solutions for taking notes. It’s a trivial problem that can be addressed in any number of ways. But it’s a problem that people spend a lot of time solving.
robotresearcher 9y ago
Existing start ups can't. But if you are a well-known AI researcher, or the student of one, you start your own company with students and friends and get your team bought for the talent.
s73v3r_ 9y ago
Stop wasting money on lavish offices and bro-ish perks, and rather put that money toward salaries.
- vinceguidry 9y ago
  You'd be amazed how little impact spreading that wealth around in the form of salaries will actually make on an individual salary. And on just how much those offices and perks actually contribute to company image. Coders should stop being so mercenary.
  - s73v3r_ 9y ago
    "Coders should stop being so mercenary." Why?
    - vinceguidry 9y ago
      Because it makes everyone less civil.
      - s73v3r_ 9y ago
        I strongly disagree. And given that I'm working for a company who's entire purpose is to make money, I fail to see why I should not do the same. Nothing good comes from me forgoing making all that I can make.
        vinceguidry 9y ago
        You'll make a lot more money just starting your own business. Like, a ridiculous amount more. Then when you start hiring, you'll understand why attitudes like yours are toxic.
        s73v3r_ 9y ago
        Again, I'm failing to see why you're advocating for a business to make all the money it can, but why you decry the same for employees. Double standard much?

They can’t, and don’t. The secret is that experienced PhDs (mostly) dominate the high end of “AI” hiring, but don’t have much title or departmental differentiation from people who are “only” specialized software engineers in top tech companies. But this isn’t very well known, large companies want to recruit as much talent as they can regardless of role, and startups want to compete on paper - therefore, you have the following effects: 1. Startups give whatever sexy title they want to the people they can afford, which makes titles fairly useless, because they almost never can afford the talent commanding “sky-high” salaries. 2. Within large tech companies like Google and Facebook, it’s hard to immediately tell which of the many data sciencey, machine learning-y titles correspond to the truly stratospheric salaries versus the engineers that work with those roles. For some teams, like DeepMind, Google Brain or FAIR, it’s easier to tell. But for others it’s a mixed bag. For comparison, see the fashionable term of art “quant” in the financial industry, which has similarly devolved into marketing and a bimodal distribution. As a rule of thumb, you generally can’t trust AI titles or salaries at startups unless those startups are really known for their talent; further, you can safely assume that, at companies capable of paying for top talent, the very impressive salaries belong to titles which seem the most exotic and out of reach for general engineers in the job description. Fortunately startups don’t really need to compete for top talent as a genuine technological differentiator, they just need to engage in signaling, so this is mostly a non-problem. Startups almost never have problems usefully improved by the cutting edge of machine learning research, and can instead use off the shelf tools and existing software to accomplish the same things. Frankly, it’s exceptionally rare for a startup to even have the massive data, pipeline and munging infrastructure requisite for actual research.

pm90 9y ago
This actually makes a lot of sense. I have a lot of friends employed as Data Scientist or Data Engineers who don't seem to be able to explain exactly what they do, or describe what "research" they are doing. From what I understand, it seems like they are designing pipelines that ingest data, run an off the shelf AI algorithm and display nice graphs. There is a lot of pipelines you can design for different kinds of data so I imagine they always have something to do.
salmonfamine 9y ago
Is this not the impetus behind the "data engineer" title that's been thrown around lately?
mr_toad 9y ago
It’s not just startups. Big business and government have slapped the ‘data scientist’ label on anyone who can drum up a chart in Excel. As Napoleon said: titles don’t honour men, men honour titles.

svantana 9y ago

In my experience, the best scientists are not motivated by money, at least not beyond enough to provide a comfortable lifestyle. For me it's much more important to work on interesting problems in a good team. Also, startups can provide an exhilarating feeling of 'anything is possible' which you rarely get at a large corporation.

Spooky23 9y ago

You don't. You sell solutions. In most enterprises, 90% of problems can be solved by somebody who can get phone calls answered, a $20/hour intern and Excel.

sgt101 9y ago
I think that's a sign of enterprise dysfunction - problems that can be solved in that way aren't real problems, they are neglect and delinquency.
- Spooky23 9y ago
  At some level, sure. But... Consider the wide variety of solutions for taking notes. It’s a trivial problem that can be addressed in any number of ways. But it’s a problem that people spend a lot of time solving.

robotresearcher 9y ago

Existing start ups can't. But if you are a well-known AI researcher, or the student of one, you start your own company with students and friends and get your team bought for the talent.

s73v3r_ 9y ago

Stop wasting money on lavish offices and bro-ish perks, and rather put that money toward salaries.

vinceguidry 9y ago
You'd be amazed how little impact spreading that wealth around in the form of salaries will actually make on an individual salary. And on just how much those offices and perks actually contribute to company image. Coders should stop being so mercenary.
- s73v3r_ 9y ago
  "Coders should stop being so mercenary." Why?
  - vinceguidry 9y ago
    Because it makes everyone less civil.
    - s73v3r_ 9y ago
      I strongly disagree. And given that I'm working for a company who's entire purpose is to make money, I fail to see why I should not do the same. Nothing good comes from me forgoing making all that I can make.
      - vinceguidry 9y ago
        You'll make a lot more money just starting your own business. Like, a ridiculous amount more. Then when you start hiring, you'll understand why attitudes like yours are toxic.
        s73v3r_ 9y ago
        Again, I'm failing to see why you're advocating for a business to make all the money it can, but why you decry the same for employees. Double standard much?