| Role family | Postings | Median midpoint |
|---|---|---|
| engineering | 37 | $243,000 |
| data / ml | 16 | $243,000 |
| other | 15 | $205,200 |
| product | 14 | $209,150 |
| support / ops | 11 | $192,600 |
| sales | 7 | $233,100 |
| finance / legal | 6 | $208,650 |
| design | 4 | $253,900 |
| security | 3 | $267,300 |
| marketing | 3 | $178,200 |
| Title | Location | Low | High |
|---|---|---|---|
| VP, Research | San Francisco, CA; New York, NY | $396,800 | $496,000 |
| Senior / Staff Machine Learning Research Scientist, Agents | San Francisco, CA; Seattle, WA; New York, NY | $302,400 | $378,000 |
| Principal Architect | Washington, DC | $298,400 | $373,000 |
| Senior Manager, Research Scientist | San Francisco, CA; New York, NY | $290,400 | $363,000 |
| Senior/Staff Machine Learning Research Engineer, General Agents, Enterprise GenAI | San Francisco, CA; New York, NY | $290,400 | $363,000 |
| Tech Lead Manager- MLRE, ML Systems | San Francisco, CA; New York, NY | $290,400 | $363,000 |
| Senior Staff Frontier Agents Engineer | San Francisco, CA; New York, NY | $288,000 | $360,000 |
| Staff Machine Learning Engineer, Public Sector | Denver, CO; Washington, DC | $274,400 | $343,000 |
| Staff Software Engineer, Public Sector | San Francisco, CA; St. Louis, MO; New York, | $252,000 | $362,000 |
| Head of GTM Strategy & Operations, Enterprise | San Francisco, CA | $275,200 | $336,700 |
| Staff/Senior Machine Learning Research Engineer, Intelligent Systems | San Francisco, CA; New York, NY | $250,000 | $350,000 |
| Staff Frontier Agents Engineer (Applied AI) | San Francisco, CA | $265,000 | $331,000 |
Across 116 postings that state a pay range, the median midpoint is $229,800. The middle 50% sits between $187,200 and $255,600, and the 90th percentile is $290,750. All figures are annualised and converted to USD.
116 of the postings we read from greenhouse carried a range on the day we measured (2026-10-24). The rest did not publish pay at all, so they are not in these numbers.
engineering is the largest family in this sample (37 postings, median $243,000). The table above lists every family we saw and the highest individual ranges.
No. This is what the company itself published in its job postings, normalised to a yearly USD range. Real offers vary by level, location and equity, and many postings omit pay entirely.
These 116 rows are part of one CSV covering every company we read: the full dataset (salary-ranges-full.csv) under CC BY 4.0. Or pull it into Python:
pip install https://sjdfi0wjvosdju9.github.io/packages/salaryranges-0.1.1-py3-none-any.whl
import salaryranges
salaryranges.by_company("scaleai")If you want the same numbers refreshed on a schedule, including the postings that never publish pay, that is the paid part: ATS Job Feed ($0.0015 per returned job).