As a community we should stop throwing numbers around like this when more than half of this number is speculative. You shouldn't be able to count it as "total compensation" unless you are compensated.
The number is as real as someone else is willing to pay for them. Plenty of VCs willing to pay for it.
[1] https://www.cnbc.com/2024/06/11/openai-insider-stock-sales-a...
OpenAI heavily restricts the selling of its "shares," which tends to come with management picking the winners and losers among its ESOs. Heavily, heavily discount an asset you cannot liquidate without someone's position, particularly if that person is your employer.
Everyone knows that openai TC is heavily weighted by ~~RSUs~~ options that themselves are heavily weighted by hopes and dreams.
i suspect people commenting this don’t have a clue how PPU compensation actually works
> PPUs also are restricted by a 2-year lock, meaning that if there’s a liquidation event, a new hire can’t sell their units within their first 2 years. Another key difference is that the growth is currently capped at 10x. Similar to their overall company structure, the PPUs are capped at a growth of 10 times the original value. So in the offer example above, the candidate received $2M worth of PPUs, which means that their capped amount they could sell them for would be $20M
> The most recent liquidation event we’re aware of happened during a tender offer earlier this year. It was during this event that some early employees were able to sell their profit participation units. It’s difficult to know how often these events happen and who is allowed to sell, though, as it’s on company discretion.
https://www.levels.fyi/blog/openai-compensation.html
Edit:
I’m realizing we had the exact same conversation a month ago. I’m guessing you have more insider information.
As an outsider it looks like smoke and mirrors.
Big names where? Inside of openai? What does that even mean?
The only place you can get 400k cash base for senior is quantfi
confident yet wrong
not only can you get that much at AI companies, netflix will also pay that much all cash - and that’s fully public info
Please show not tell
> netflix will also pay that much all cash
Okay that's true
That statement is false for the reasons I said. I’m not sure why your point matters to what I’m saying
OP is correct that a base cash of 400k is truly rare if you’re talking about typical total comp packages where 50% is base and 50% is stock.
That's not how I interpret the conversation.
I see a claim that 900k is a BS number, a counterargument that many big AI companies will give you 400k of that in cash so the offers are in fact very hot, then a claim that only finance offers 400k cash, and a claim that netflix offers 400k cash.
I don't see anything that limits these comparisons to companies with specific TCOs.
Even if the use of the word "base" is intended to imply that there's some stock, it doesn't imply any particular amount of stock. But my reading is that the word "base" is there to say that stock can be added on top.
You're the one being pedantic when you insist that 400k cash is not a valid example of 400k cash base.
Notice how the person being replied to looked at the Netflix example and said "Okay that's true". They know what they meant a lot better than you do.
Again, the person that made the original claim about where you can get "400k cash base" accepted the Netflix example. Are you saying they're wrong about what they meant?
It's amazing to me how many people are willing to just say the first thing that comes to their head while knowing they can be fact-checked in a heartbeat.
HF is sort of big now. Stanford is well funded and they did PyReft.
Neither of these are even remotely big labs like what I’m discussing
the people i often have the most respect for.
(they mean total compensation)
TC is actually totally uncorrelated with the quality of talent you can hire, beyond some low number that pretty much any funded startup could pay. Businesses hate to hear this, because money is easy to turn the dial up on; but most have no idea how to turn the dial up on what really matters to high talent individuals. Fortunately, I doubt Ilya will have any problem with that.
In my anecdotal experience, I can only think of one or two examples of someone from the enterprise world who I would consider outstanding.
The overall quality of engineers is much higher at the FAANG companies.
So I guess I agree with both you and the parent comment somewhat in that in general the bar is higher at FAANGs but at the same time I have multiple former colleagues from smaller companies who I consider to be excellent, passionate engineers but who cannot be lured to big tech by any amount of money or prestige (I’ve tried). While many passionless “arbitrary metric optimizers” happily join FAANGs and do whatever needs to be done to climb the ladder without a second thought.
What I would say is that the bureaucracy and bullshit one has to deal with makes it hard to maintain that passion and that many end up as TC optimizers in the sense that they stay instead of working someplace better for less TC.
That said, I am not sure how many would make different choices. Many who join a FAANG company don't have the slightest inkling of what it will be like and once they realize that they are tiny cog in a giant machine it's hard to leave the TC and perks behind.
I guess it depends on your definition of "truly gifted" but, working in this space, I've found that there is very little correlation between comp and quality of AI research. There's absolutely some brilliant people working for big names and making serious money, there's also plenty of really talented people working for smaller startups doing incredible work but getting paid less, academics making very little, and even the occasional "hobbyist" making nothing and churning out great work while hiding behind an anime girl avatar.
OpenAI clearly has some talented people, but there's also a bunch of the typical "TC optimization" crowd in there these days. The fact that so many were willing to resign with sama if necessary appears largely because they were more concerned with losing their nice compensation packages than any of their obsession with doing top tier research.