Research Engineer - Evals
About the role
Role focused on designing and building evaluation systems to measure data quality and outputs across a wide range of websites and formats. Own metrics, pipelines, datasets, and feedback loops from output quality to model/product decisions.
Responsibilities
- Design the metrics that define what "good output" actually means across millions of sites, formats, and edge cases
- Build the pipelines and harnesses that measure quality rigorously and at scale
- Generate and curate the datasets that make evaluation trustworthy
- Own the feedback loop from output quality back to model and product decisions
- Turn "did that work?" into an answer the whole team can act on
Qualifications
- 4+ years in ML, research engineering, or data-heavy backend, with real evaluation work
Skills
Benefits
- Salary that makes sense: $250,000–$290,000 USD/year (SF) / $210,000–$224,000 CAD/year (Toronto) based on impact
- Competitive equity
- Generous PTO: 15 days mandatory, more by request
- Parental leave: 12 weeks fully paid
- Wellness stipend: $100 USD/month
- Learning & Development: up to $1,000 USD/year
- Team offsites
- Sabbatical: 3 paid months off after 4 years

About Firecrawl
The web data API for AI
Firecrawl is a web data infrastructure platform that converts websites into clean, structured data optimized for AI applications through a simple API. Originally built as an internal tool at Mendable to solve their own data ingestion challenges, the team recognized the broader need for reliable web data extraction and transformed it into a standalone product. The platform combines web search, scraping, and AI-powered parsing into a unified solution, focusing on the core developer priorities of reliability, speed, and ease of use. By abstracting away the complexities of web data extraction, Firecrawl serves as the foundational data layer that enables AI applications to seamlessly access and process web content in the exact format they need.
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