Description
Every week, someone asks which data provider is actually best: for company records, for finding the right person, for fresh job listings. Right now the answers come from the vendors themselves. You'll build the independent version. You'll run rigorous, automated, public benchmarks of the providers in Alexandria and beyond, and publish them weekly. The same results will feed straight back into Alexandria so it learns which provider to call for which job.
This isn't our internal evals role. You're measuring the market, in public, where every number will be challenged by the vendors it ranks. You'll own it end to end: the datasets, the ground truth, the scoring, the harness, the weekly release, and the loop into Alexandria's provider selection. No one hands you a methodology. You write it, defend it, and ship it every week.
Salary Range: $250,000–$290,000 USD/year (SF) / $210,000–$224,000 CAD/year (Toronto)
Equity Range: Competitive equity. Details shared during the process.
Location: San Francisco, CA (SF HQ) or Toronto, ON (Toronto Hub). Hybrid, onsite 3+ days a week.
Equity Range: Competitive equity. Details shared during the process.
Location: San Francisco, CA (SF HQ). On-site, five days a week.
Job Type: Full-Time
Experience: 4+ years in ML, research engineering, or data engineering, with evaluation or benchmark work you've shipped
Work Authorization: Must be authorized to work in the United States or Canada. We're not able to sponsor US visas right now. For Canada, we'll consider sponsorship on a case-by-case basis through our Toronto Hub.
About the company
The company is the easiest way to turn the web into data AI agents can use. One API call converts any URL into clean, LLM-ready markdown or structured data. It's the boring-hard problem everyone building with LLMs eventually hits, solved.
We hit 8 figures in ARR in year one and more than doubled it in year two. Growth like this is rare, and we're just getting started.
We're a small team punching far above our weight. Everyone here owns a real piece of the product and company, end to end, and runs it themselves. No hiding behind process or headcount.
This is a place for people who want to work at the frontier: an AI company building the infrastructure other AI companies run on, not one bolting AI onto an existing product. We move fast, go deep, and are building the tools superintelligence will rely on to gather data from the web. That library is called Alexandria, and it starts now.