Firecrawl is the web data API to search, scrape, and interact with the web at scale. Turn any source into clean Markdown or structured data your agents can ship with. Backed by Y Combinator.
About the role
Improve ranking and relevance for Firecrawl Search, from feature engineering to model training to production Build and tune models for learning-to-rank, query understanding, and LLM-driven retrieval
What they're looking for
- You've shipped ML models into production systems and owned them after launch: deploying, monitoring, and retraining them, not handing them off
- You have real ranking or relevance-modeling experience: learning-to-rank, recommendations, or search quality
- You're comfortable in large, data-heavy systems: query logs, pipelines, and datasets that don't fit in memory
- You write production-quality code (Python at minimum) and can work inside a real backend codebase
- You're rigorous about measurement. You've designed and analyzed A/B tests and know when a lift is real
- You can communicate results clearly to the team: what shipped, what moved, and what to do next
More about this role
You'll build the ML behind Firecrawl: the models and the systems that serve them. That starts with search: training and shipping the ranking and relevance models for one of our fastest-growing products, then extending that work across extraction quality and LLM-driven features. You'll also own how we measure: A/B testing launches and building the experimentation frameworks the whole team ships against. If you ship models into production, whether your title says ML engineer or data scientist, this is for you.
Equity Range: Competitive equity. Details shared during the process.
Job Type: Full-Time
Experience: 3+ years building ML or data-heavy systems in production
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.
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...
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