We did something different. We pulled salary data from 37,943 startup job listings — not self-reported, not estimated, but actual compensation ranges posted by companies in their job descriptions. The results are more interesting than the usual list, because they reveal what startups are actually willing to pay right now, not what people claim they earn.

The methodology (because it matters)

Our data comes from 8,000+ startups that post jobs through major ATS platforms. We extract the maximum salary from posted compensation ranges. This means our numbers skew toward the top of each band — the number a company would pay for an exceptional candidate, not the floor for a junior hire.

We only included roles with at least 20 data points to avoid small-sample noise. All figures are annualized USD.

The top 10 highest-paying titles

Here's what the data says:

1. Research Scientist — $300,000 median The highest-paying title at startups isn't a management role. It's the individual contributor who pushes the frontier of what's technically possible. These roles are concentrated at AI labs and deep-tech companies — places like OpenAI, Anthropic, and the autonomous vehicle companies. The catch: you typically need a PhD and published research. There are only 22 open positions with salary data, which tells you how rare and how valued these roles are.

2. Member of Technical Staff — $300,000 median This title has become the prestige engineering designation at top-tier startups. It signals "we don't have traditional engineering levels, and everyone here is exceptional." Companies like Anthropic, OpenAI, and a handful of elite startups use this title. With 26 open positions, the competition is intense but the compensation reflects it.

3. Software Engineer, Infrastructure — $280,000 median Infrastructure engineers who keep distributed systems running at scale command a premium over generalist engineers. The "infrastructure" qualifier adds roughly $30K-$50K to the median compared to a generic "software engineer" title. These roles require deep expertise in systems design, reliability engineering, and usually Kubernetes or similar orchestration tools.

4. Staff Machine Learning Engineer — $272,500 median The "staff" prefix in ML engineering puts you in rarefied air. These are the people who design the model architectures, optimize training pipelines, and make the technical decisions that determine whether an AI product actually works. The salary premium over a regular ML engineer ($220K median) is about $50K — the reward for being the person the team turns to when things break.

5. Staff Software Engineer — $250,000 median With 151 open positions, this is the most common high-paying title on the list. Staff engineers are the technical backbone of engineering organizations — they set architectural direction, mentor senior engineers, and solve the problems that nobody else can. The role exists at companies of all stages, from Series A to pre-IPO.

6. Infrastructure Engineer — $250,000 median Similar to #3 but without the "software" qualifier, these roles often include a broader scope: cloud infrastructure, CI/CD pipelines, developer tooling, and platform engineering. The $250K median reflects the market reality that keeping systems reliable is as valuable as building new features.

7. Applied AI Engineer — $250,000 median The hottest title of 2026. Applied AI engineers take foundation models and make them useful — building RAG pipelines, fine-tuning models for specific domains, and integrating LLMs into production applications. With 34 open positions at this salary level, it's the intersection of high demand and scarce supply.

8. Staff Product Designer — $240,000 median Design compensation at startups has quietly caught up with engineering. A staff product designer at a well-funded startup earns more than most senior engineers. These roles require 8-10+ years of experience and a portfolio that demonstrates business impact, not just visual craft. With 47 open positions, the market for senior design talent is real.

9. Engineering Manager — $240,000 median The classic people-management path for engineers. Engineering managers at startups typically manage 5-10 engineers and are expected to remain technically hands-on. The $240K median reflects the dual burden: you're responsible for both the team's output and the team's wellbeing. With 101 open positions, this is the most available high-paying role on the list.

10. Principal Product Manager — $240,000 median The most senior IC product role at most startups. Principal PMs own entire product areas or strategic initiatives. They're the people who decide what gets built next and why. The $240K median is competitive with engineering manager compensation, which reflects the growing recognition that product strategy is as valuable as technical execution.

The function-level view

Zooming out from specific titles, here's how entire functions compare:

Engineering, Product, and Data are tied at a $210,000 median — but Data has the highest ceiling, with a p90 of $325,000 compared to Engineering's $300,000 and Product's $288,000. If you want the highest possible compensation and you're choosing between career paths, the data suggests that data science and data engineering have the steepest upside.

Design comes in at $175,000 median, which is lower than engineering but the gap narrows significantly at the senior level. A staff designer ($240K) earns the same as an engineering manager.

Sales has a $174,000 median, but this is base salary only. With commission and bonuses, top sales performers at startups regularly out-earn everyone except the most senior engineers.

Operations has the lowest median at $140,000, but the p90 is $250,000 — meaning the top ops leaders at startups earn competitive compensation. The range is just wider than other functions.

What the data doesn't tell you

Salary data from job listings has real limitations. It doesn't include equity, which at early-stage startups can be worth anywhere from zero to life-changing. It doesn't capture signing bonuses, which are common for senior hires. And it reflects what companies are willing to post publicly, which may be different from what they actually pay after negotiation.

The numbers also skew toward US-based roles, since international startups are less likely to post salary ranges. A "software engineer" role in London or Berlin will typically pay 30-50% less than the same role in San Francisco, even at the same company.

The practical takeaway

If you're optimizing for compensation at startups, the data points to a few clear strategies:

Go deep, not broad. The highest-paying roles are specialists, not generalists. "Staff ML Engineer" pays $50K more than "ML Engineer." "Software Engineer, Infrastructure" pays $70K more than "Software Engineer." Specificity is rewarded.

The IC path pays as well as management. Staff and principal IC roles ($240K-$300K) match or exceed manager compensation ($240K). You don't have to manage people to maximize your earnings.

AI is the current premium. Applied AI Engineer, Staff ML Engineer, and Research Scientist are all in the top 7. If you're early in your career and choosing a specialization, the market is clearly signaling where the demand is.

And if you're in ops, marketing, or finance and feeling underpaid relative to engineering — the gap is real at the median, but it narrows dramatically at the senior level. A VP of Marketing or Head of Revenue Operations at a growth-stage startup can earn $250K+, which is competitive with all but the most senior engineering roles.

The startup salary market in 2026 is paying a premium for depth, technical skill, and AI expertise. But it's also paying more than ever for the non-engineering roles that actually scale a business. The data is right here — use it to negotiate accordingly.