It seems like even a PhD doesn't get you close to $300k at most research scientist type roles, with the exception of the big tech names.

Yup. At least with a physics PhD, it seems you make less than the software engineers sitting next to you even at a physics-centric company. Unfortunately, most people out of grad school are just happy to be making more and don’t exercise much negotiating power, suppressing wages for everyone.

You don't even need a masters to make $300K doing CRUD in big tech.

I don't have a bachelor's and I take home $300k

What a huge contrast lol. $335k salaries vs $3.99 per prompt.

$335K/yr is 335 $4 prompts per standard workday, about 1/minute, allowing for breaks.

How fast can you generate prompts?

I'm using AI to make my AI prompt.

Money Please!!!

Yep, just type: "teach me prompt engineering".

To me it sounds like an Accenture submarine. "Come and let us charge you for doing something you can do yourself". Maybe I'm just a cynical techie, but I don't think some guy who hasn't studied anything technical is going to provide any value in talking to the AI. Chances are you will do much better with domain knowledge, eg a dev asking it for code, or a lawyer asking it for legal precedents.

Linguistics (if you did it right) and Cognitive Science is deeply "technical" in the sense that you'll be knee deep in Tree Structure, Lexiostatistics, and Probability Theory to create datasets, reproducible grammars, and encode meaning.

Sure, but Phelps is a history grad.

True, but that's more an artifact of Accenture's hiring practices in the UK (concentrating on hiring from a handful of Russell Group Unis where Engineering doesn't have much of a reputation compared to humanities/social science. on a separate note, the only notable NLP/AI groups in the UK are at Cambridge, Oxford, Edinburgh, and Imperial College, and most of them filter into SWE).

The equivalent roles in the US will end up hiring people with a background in Linguistics, Cognitive Science, or Library and Information Sciences. This is seen in Anthropic's job listing for example.

You're on to something here.

I really believe that in the long run, it will be the tech oriented domain experts who are the valuable ones. That's really who we've found we need at nearly every implementation step of our AI strategy. You need to know what data to get in your target domain. How to interpret that data. Some method of scoring that data. And all that's just table stakes. It goes on and on. Someone with a tech background is just not going to know about stenosis calculations the way a cardiologist will. Or legal precedents like a lawyer does. Or compressive strength values like a civil engineer does. And so on and so forth.

AI generalists are also enormously valuable, but only to the Google, Microsofts, and OpenAIs of the world. Among those competing to make generalist AIs, it will be winner take all I'm afraid. Majority of the jobs created for generalist AI guys will be at big tech cos. The vast majority of the jobs generated in AI outside of big tech, will rely heavily on specialized knowledge of the domain experts.

I even think colleges might want to consider adjusting the educational curriculum so that some cs knowledge is taught more like writing class. It's just something professionals will need to be familiar with and know how to do in the future. But not all that valuable in and of itself unless you can be one of the top guys.

Someone who only knows CS? no other specialized knowledge?

And they don't have the math chops of the OpenAI guys?

Sorry, but you're just not going to be all that valuable in the future. Salaries for those kinds of people will start a slow decline for sure.

Probably the job posting was just to provide legal cover for some spectacularly indulgent act of nepotism, like hiring the CEO's otherwise useless frat boy son after he got kicked out of school for cocaine and sexual abuse. I'm surprised Truth Social hasn't hired Don Jr. to write conspiracy theories and press releases by whispering to ChatGPT3 yet.

In my experience this is spot on. We hired the COOs son and paid him $200k+ various stipends.

"Prompt engineering" is a made up thing. There's not some magic William Gibson prompt cowboy who through some innate intuition can master prompts the way nobody else can.

It's a deterministic model. There's plenty of interesting explainability work, or however you want to frame it, to be done understanding the connection between different prompts and outputs. But it's clearly in the province of real ML researchers who have experience on the area, and will approach it scientifically. 335k for someone good at that is not unusual at all, they have lots of options.

Prompt engineering is more prompt chaining which is actively being researched so it is a thing. https://github.com/hwchase17/langchain

Point is, there's some black box, lay-version of playing with prompts, and there's a real study of how the prompt affects output by people who understand the workings of the model. Presumably they're hiring for the latter and not some kid with intuition, and therefore the headline is sensational because the story is that a job for a highly educated and specialized scientist pays well.

> It's a deterministic model

What is? Aren't large language models very specifically not deterministic? It's impossible to reliably predict their response to a given prompt until you actually run the prompt, even with the temperature parameter set to zero (and often temperature is higher than zero in practical deployments).