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Firecrawl

Research Engineer - Evals

Firecrawl is hiring a Research Engineer - Evals for a remote role open to applicants in United States. It pays $250k-$290k a year and Level rates it ; you can apply on Firecrawl.

Level's read on this job

  • Works on AI ●●●○ is how Level rates this role: the daily work is on AI products, without building the model.
  • This is listed as a remote role.
  • The posting mentions AI agents among its tools and skills.
  • Firecrawl has 29 other open roles on Level.

AI in this role

ai-agents
Research Engineer - Evals

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: $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.

Job Type: Full-Time

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

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 192k+ 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.

Our Values
  • Bias to action: We move fast, ship hard, and don’t wait to be told.

  • Realistic about AI: We’re clear-eyed about what AI can and can’t do, and we keep pushing to use it where it actually works.

  • All in: The next few years matter a lot, and we’re all in for them.

  • Human connection: As intelligence gets cheaper, relationships with customers, partners, and each other matter more.

What You'll Do
  • 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

What We're Looking For
  • You have the engineering depth to build real evaluation systems, not just run existing ones

  • You care deeply about what "good" means and how to measure it rigorously

  • You're comfortable owning ambiguous problems where the metric itself has to be invented

  • You move fast and close the loop. You'd rather ship, measure, and iterate than perfect on paper

What We're Not Looking For
  • Someone who only wants to run benchmarks someone else designed

  • A pure researcher who won't build the systems, or a pure engineer who won't think about methodology

  • Someone who needs a fully-specced ticket to start

A Note On Pace

We operate at an absurd level of urgency because the window for what we're building won't stay open forever. If that excites you, keep reading. If it doesn't, no hard feelings, but this role probably isn't for you.

Benefits & Perks

Available to all employees

  • Salary that makes sense: $250,000–$290,000 USD/year (SF) / $210,000–$224,000 CAD/year (Toronto), based on impact, not tenure

  • Own a piece: Gain competitive equity in what you're helping build

  • Generous PTO: 15 days mandatory, anything after 24 days, just ask (holidays excluded). Take the time you need to recharge

  • Parental leave: 12 weeks fully paid, for all parents

  • Wellness stipend: $100 USD/month for the gym, therapy, massages, or whatever keeps you human

  • Learning & Development: Expense up to $1,000 USD/year toward anything that helps you grow professionally

  • Team offsites: A change of scenery, minus the trust falls

  • Sabbatical: 3 paid months off after 4 years, do something fun and new

Available to US-based full-time employees

  • Full coverage, no red tape: Medical, dental, and vision (100% for employees, 50% for partner and kids). No weird loopholes, just care that works

  • Life & Disability insurance: Employer-paid basic life and AD&D, short-term disability, and long-term disability. Coverage for life's curveballs

  • Virtual care and a health guide: Teladoc for the couch doctor visit, plus Rightway to answer coverage questions and fight billing errors for you

  • Mental health: Talkspace, therapy and psychiatry on your schedule

  • Fertility and family building: Carrot, covering you and your partner

  • EAP: Free confidential counseling, legal and financial consults, and online will prep through Guardian

  • 401(k) plan: Retirement might be a ways off, but future-you will thank you

  • Pre-tax benefits: HSA, FSA, and commuter benefits to help your wallet out a bit

  • Supplemental options: 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

  • Full coverage, no red tape: 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. Coverage for life's curveballs

  • Virtual care: Dialogue Premium, so you can see a doctor or nurse from your couch, any hour

  • Mental health: Talkspace Elite, therapy and psychiatry on your schedule

  • Fertility and family building: Carrot, covering you and your partner

  • Retirement: Group RRSP through Wealthsimple, so future-you can thank you

Available to SF-based employees

  • SF HQ perks: Snacks, drinks, team lunches, intense ping pong, and peak startup energy

  • E-Bike transportation: A loaner electric bike to get you around the city, on us

Available to Toronto-based employees

  • Toronto Hub perks: Snacks, drinks, team lunches, glass-walled views down University Avenue, and a home base steps from Union Station

  • Transit, covered: A PRESTO card loaded for GO Transit, subway, and streetcar, plus station parking if you drive to the train. Winter-proof, on us

Interview Process

Application Review: Send us your work and a quick note on why this excites you. Show us what you've built: eval systems, metrics you designed, datasets you created, quality problems you measured. We care about what you've shipped, not where you went to school.

Intro Chat (~25 min): A quick conversation to get to know each other before we go deep. We'll talk about what you've been working on, what drew you to Firecrawl, and what you're looking for in your next role. Time for your questions too.

Technical Chat (~45 min): We'll dig into a real problem from our world: how you'd measure whether messy web output is actually "good," and build the system to prove it. Come ready to think out loud. We care how you reason, not whether you memorized the answer.

Founder Chat (~25 min): Culture, pace, ownership, and how you like to work. Time for your questions too.

Paid Work Trial (~40 Hours): Work with the team on a real, scoped evaluation problem, paid at a contractor rate. It's the truest signal for both sides. You see what building at Firecrawl actually feels like, and we see how you ship. Remote-friendly, and we'll flex around your current commitments.

Decision: We move fast after the trial.

If you care about what "good" actually means and have the engineering depth to measure it, you should join us.

👉 Apply now.

How we rate this

Research Engineer - Evals at Firecrawl rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.

Classification

Works on AI. The daily work is on AI products, without building the model.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI agents

Questions you could be asked

  1. How do you decide when an AI agent can act on its own versus asking for approval first?
  2. Describe a typical day in a role like this one: which parts run through AI directly?
  3. If you removed AI from this role, what would be left, and how do you decide what still needs a human?

Adapt your resume

  • List these exact terms on your resume: AI agents. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.

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