Research Engineer

RESEARCH ENGINEER

You'll build the evaluation systems that tell us whether Firecrawl actually works. That sounds simple. It isn't. Our core promise, convert any URL into clean, structured, LLM-ready data reliably, is hard to measure rigorously across millions of different websites, formats, and edge cases. As the systems we're measuring get more complex, the question "did that work?" gets harder, not easier.

This isn't an eval role where you inherit a framework and run benchmarks. You'll design the metrics, build the pipelines, generate the datasets, and own the feedback loop from output quality back to model and product decisions. If you care about what "good" actually means and have the engineering depth to measure it, this is the role.

Salary Range: $210,000–$275,000/year (Range shown is for U.S.-based employees in San Francisco, CA. Compensation outside the U.S. is adjusted fairly based on your country's cost of living.)

Equity Range: Competitive equity — details shared during the process.

Location: San Francisco, CA (Hybrid, on-site required)

Job Type: Full-Time

Experience: 4+ years in ML, research engineering, or data-heavy backend, with real evaluation work

Visa: Must be legally authorized to work in the United States. We're not able to sponsor visas right now, though that may change down the line.

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 - 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. We have 147k+ GitHub stars, 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 beh...