I went through this exercise myself when someone on a forum claimed "everyone I know in AI makes $1M+." It's junk. Here's what the data actually says:
Why does this gap matter? Because the $100M narrative distorts career decisions. People chase "AI exit" dreams and pass on solid, well-paid roles that are actually attainable. The $824k job exists — it's a real posting, a real team, real responsibilities. But it's one position, and it's still a W-2, not a lottery ticket.
Top advertised base+bonus+equity:$824k (a senior research role at one of the big labs)** Typical "elite" AI engineer, 5+ years:$350k – $550k total comp New grad AI/ML roles:$150k – $220k at top firms The $100M claim:**usually founders or early equity holders, not hired employees
Why does this gap matter? Because the $100M narrative distorts career decisions. People chase "AI exit" dreams and pass on solid, well-paid roles that are actually attainable. The $824k job exists — it's a real posting, a real team, real responsibilities. But it's one position, and it's still a W-2, not a lottery ticket.
The closest real-world path to those 8-figure numbers is:
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Join a pre-IPO lab or startup at the founding-engineer level. Equity, not salary, is the multiplier.
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Build something demonstrably useful — a deployed agent, an eval harness, a fine-tuning pipeline that ships. Papers alone don't get you the 7-figure packages anymore.
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Be willing to relocate or go remote-first. The $824k role wasn't in San Francisco; it was in a market with less talent density.
So yes, AI is the best-paid engineering niche right now. But the useful question isn't "how big can the number get" — it's "what compensation is actually being offered today." $824k is a great answer. Everything above that is salesmanship.
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T
The real kicker is equity. A $400k base sounds great until you realize the stock isn't worth the paper it's printed on. Never count unvested shares as salary.
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