Research Engineer - Benchmarks

RESEARCH ENGINEER - BENCHMARKS 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: Open to candidates already authorized to work in the US or Canada. In the US, we also support H-1B transfers, F-1 OPT and STEM OPT, TN (Canada and Mexico), and E-3 (Australia). We’re not able to sponsor new H-1B visas for candidates outside the US. For Canada, we’ll consider work permit sponsorship case by case through our Toronto Hub. ABOUT FIRECRAWL Firecrawl 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. In September 2026, we raised a $75M Series B led by Smash Capital, and we're spending it building the largest repository of knowledge in the world. We hit 8 figures in ARR in year one and more than doubled it in year two. We have 187k+ GitHub stars, putting us in the top 40 repositories of all time, and developers, agents, and category-defining AI companies build on us every day. 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. WHAT YOU'LL DO - Design and run head-to-head benchmarks of data providers against verified ground truth. For example: - Apollo vs. FullEnrich vs. DataLegion on company details. - FullEnrich vs. DataLegion on finding the right person and their current employer and title. - Built In vs. ZipRecruiter on relevant, fresh, non-duplicate job listings. - Build and maintain the test datasets and ground truth, and keep them from going stale or leaking. - Own the automated harness and the weekly benchmark release. Every run has to be reproducible, versioned, and defensible. - Measure what buyers actually care about: accuracy, coverage, freshness, speed, and cost. - Work with marketing to ship public leaderboard pages that are useful and hold up under scrutiny. - Close the loop into Alexandria so benchmark results change which provider gets called for what. - Keep expanding the categories we benchmark, inside Alexandria and beyond it. WHAT WE'RE LOOKING FOR - You've shipped evals or benchmarks, and you can explain exactly why your results were trustworthy. - You've done this somewhere that matters: a frontier lab, a data company like Scale, Surge, micro1 or Mercor, a third-party benchmark org, or a public benchmark project. OSS contributors very welcome. - You're strong in Python and API integrations, and comfortable with messy vendor APIs, rate limits, and inconsistent schemas. - You know how to build test sets and scoring methods: sampling, labeling, inter-rater agreement, and when to trust an LLM judge and when not to. - You use AI heavily and keep upgrading your own workflow. You ship without waiting for instructions. - You write findings clearly for engineers, marketers, and the vendors on the other side of the leaderboard. WHAT WE'RE NOT LOOKING FOR - Someone who wants to run benchmarks someone else designed. - Someone who picks the metric that makes the story look good. Our numbers have to survive the vendors