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. You’ll run rigorous, automated, public benchmarks of the providers in Alexandria and beyond, and publish them weekly. You’re measuring the market, in public, where every number will be challenged by the vendors it ranks. You write it, defend it, and ship it every week.

250,000–$290,000 USD/year (SF) / $210,000–$224,000 CAD/year (Toronto)

Equity Range: Competitive equity. San Francisco, CA (SF HQ) or Toronto, ON (Toronto Hub). Hybrid, onsite 3+ days a week.

Equity Range: Competitive equity. On-site, five days a week.

Full-Time

4+ years in ML, research engineering, or data engineering, with evaluation or benchmark work you’ve shipped 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 spending it building the largest repository of knowledge in the world. 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. 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.





Design and run head-to-head benchmarks of data providers against verified ground truth. Build and maintain the test datasets and ground truth, and keep them from going stale or leaking. Work with marketing to ship public leaderboard pages that are useful and hold up under scrutiny.

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. You’re robust in Python and API integrations, and comfortable with messy vendor APIs, rate limits, and inconsistent schemas.

You use AI heavily and keep upgrading your own workflow. You ship without waiting for instructions. Someone who needs a fully specced ticket, or a quarter, to ship the first result. We operate at an absurd level of urgency because the window for what we’re building won’t stay open forever. 250,000–$290,000 USD/year, / $210,000–$224,000 CAD/year (Toronto), based on impact, not tenure Gain competitive equity in what you’re helping build 15 days mandatory, anything after 24 days, just ask (holidays excluded).

Parental leave: Expense up to $1,000 USD/year toward anything that helps you grow professionally Available to US-based full-time employees Medical, dental, and vision (100% for employees, 50% for partner and kids).





Life & Disability insurance: Employer-paid basic life and AD&D;, short-term disability, and long-term disability.

Virtual care and a health guide: Fertility and family building: EAP: Free confidential counseling, legal and financial consults, and online will prep through Guardian Retirement might be a ways off, but future-you will thank you Pre-tax benefits: HSA, FSA, and commuter perks to help your wallet out a bit Extra life and AD&D;, accident, critical illness, hospital indemnity, plus pet, legal, and identity protection through MetLife Available to Canada-based full-time employees Extended health, dental, and vision through Manulife (Diamond, the top tier), 100% employer-paid for you, your partner, and your kids Life & Disability insurance: Employer-paid life, AD&D;, short-term disability, and long-term disability.

Virtual care: Fertility and family building: Retirement: Toronto Hub perks: Snacks, drinks, team lunches, glass-walled views down University Avenue, and a home base steps from Union Station We care about what you’ve shipped, not where you went to school.

Intro

Chat (~25 min): We’ll cover what you’ve been working on, what drew you to Firecrawl, and what you want next.

Technical

Chat (~45 min): Workflow Chat (~30 min): Show us how you actually work: your AI tools, your setup, and a recent thing you shipped faster than you would have a year ago.

Founder

Chat (~25 min): Ship a small benchmark end to end on a real provider category, paid at a contractor rate. It’s the truest signal for both sides. Remote-friendly, and we’ll flex around your current commitments. If you want to be the person the whole market checks before picking a data provider, you should join us. #

📌 Research Engineer, Machine Learning (Toronto)
🏢 Firecrawl
📍 Toronto