| Role family | Postings | Median midpoint |
|---|---|---|
| data / ml | 3 | $292,500 |
| sales | 1 | $325,000 |
| finance / legal | 1 | $215,000 |
| marketing | 1 | $205,000 |
| Title | Location | Low | High |
|---|---|---|---|
| Founding Go-To-Market (GTM) | Palo Alto HQ | $200,000 | $450,000 |
| ML Engineer, Inference & Optimization | US remote | $250,000 | $350,000 |
| Research Scientist, Post-Training — Video Generation | US remote | $185,000 | $400,000 |
| Research Scientist, Data | US remote | $185,000 | $400,000 |
| Head of Finance | Palo Alto HQ | $180,000 | $250,000 |
| Head of Growth | Palo Alto HQ | $160,000 | $250,000 |
Across 6 postings that state a pay range, the median midpoint is $292,500. The middle 50% sits between $234,375 and $298,125, and the 90th percentile is $312,500. All figures are annualised and converted to USD.
6 of the postings we read from ashby 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.
data / ml is the largest family in this sample (3 postings, median $292,500). 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 6 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("pika")
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).