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Firecrawl

Head of Research

Posted 7 Days Ago
Be an Early Applicant
In-Office or Remote
2 Locations
200K-300K Annually
Senior level
In-Office or Remote
2 Locations
200K-300K Annually
Senior level
Lead the research function at Firecrawl to enhance core technology in search and information retrieval, ensuring output is production-ready. Build and manage a high-output research team and collaborate with engineering to directly impact product development.
The summary above was generated by AI
Head of Research

You'll build and lead the research function at Firecrawl — the team responsible for making our core technology meaningfully better than anything else on the market. That means search, ranking, information retrieval, fine-tuning, and model training applied to the hardest problems in web data extraction. This isn't a research lab. Everything you build ships to production and runs at scale. You'll start by doing the work yourself, then hire a small team of people who are smarter than you.

Salary Range: $200,000–$300,000/year (Range shown is for U.S.-based employees. Compensation outside the U.S. is adjusted fairly based on your country's cost of living. You can explore how we calculate this here: https://www.firecrawl.dev/careers/compensation.)

Equity Range: Up to 0.25%

Location: San Francisco, CA or Remote (Americas, UTC-3 to UTC-10)

Job Type: Full-Time

Experience: 5+ years in applied research, ML engineering, or search/IR — with production systems at scale

Visa: US Citizenship/Visa required for SF; N/A for Remote

About Firecrawl

Firecrawl is the easiest way to extract data from the web. Developers use us to reliably convert URLs into LLM-ready markdown or structured data with a single API call. In just a year, we've hit 8 figures in ARR and 90k+ GitHub stars by building the fastest way for developers to get LLM-ready data.

We're a small, fast-moving, technical team building essential infrastructure super-intelligence will use to gather data on the web. We ship fast and deep.

What You'll Do
  • Own the research roadmap: Define what Firecrawl needs to build to stay technically ahead — across search, ranking, relevance, information retrieval, fine-tuning, and model training. You'll decide where we invest research effort and what makes it into production.

  • Ship research to production at scale: Every project you lead ends with code running in prod, serving real customers at real volume. You'll work closely with the engineering team to make sure research output is production-grade — fast, reliable, and maintainable.

  • Go deep on search and IR: Build and improve the systems that power how Firecrawl finds, ranks, indexes, and retrieves web content. This is core to the product and core to the moat. You'll own freshness, dedup, query understanding, and incremental indexing at a scale that matters.

  • Fine-tune and train models: Build and operate training pipelines that improve Firecrawl's extraction quality, content understanding, and data structuring. You know how to get from raw data to a model that moves a metric in production.

  • Build and lead a high-output research team: You'll start hands-on, then hire 2–4 researchers who are deeply technical and ship fast. You know how to find and attract people who are smarter than you — and how to create an environment where they do their best work.

  • Collaborate across engineering and product: Research doesn't happen in a vacuum. You'll work with Nick and the engineering team to prioritize research investments that directly improve the product, and with the growth team to understand what customers need.

What We're Looking For

Someone who has shipped research to production at scale. You've taken research from idea to experiment to deployed system — not once, but repeatedly. You know the difference between a promising result in a notebook and a system that works at production volume with real-world data. You optimize for impact, not publications.

Deep knowledge across search, IR, fine-tuning, and model training. You don't just know one corner of ML. You've built search indexes, trained ranking models, fine-tuned LLMs, and operated the infrastructure that supports all of it. You can go deep on any of these and you know how they connect.

Experience building and leading small, high-output research teams. You've built research teams at startups — ideally Series A through Series D, in the 10-to-50-person range. You know how to hire well, set direction without micromanaging, and create a culture where great researchers want to stay. Small team, big output is your default mode.

Can recruit people smarter than them. This is non-negotiable. You have a network of strong researchers and you know how to sell a mission. You're not threatened by talent — you're energized by it. The team you build will define Firecrawl's technical ceiling.

Production-minded. You care about latency, cost, reliability, and maintainability as much as model quality. You've debugged production ML systems at 3am and you've made hard tradeoffs between accuracy and speed. You know that research that doesn't ship is research that doesn't matter.

Backgrounds that tend to do well: Applied research leads at search companies, data infrastructure startups, or AI labs with a production focus. ML engineering managers who built search/ranking/IR systems at scale. Technical founders who built and shipped ML-powered products. Senior researchers who got frustrated with academia and wanted to ship.

What We're NOT Looking For

Pure academics. If your best work is a citation count and you've never shipped a model to production, this isn't the role. We respect the research — we just need it to run in prod.

Big-company research managers. If you led a 30-person team at Google Brain and your job was writing strategy docs and attending reviews, you'll be frustrated here. This role is hands-on for the first 6+ months. You write code, you train models, you debug pipelines.

ML generalists who haven't gone deep on search/IR. We need specific depth in information retrieval, ranking, indexing, and search infrastructure. If your experience is mostly in computer vision, NLP classification, or recommendation systems without search/IR, this isn't the right fit.

People who need perfect data and clean infrastructure to do good work. The data is messy. The infrastructure is evolving. If you need everything set up before you can be productive, you'll stall here. We need someone who builds the infrastructure as they go.

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 — $200,000–$300,000/year, based on impact, not tenure

  • Own a piece — Up to 0.25% 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 moms and dads

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

  • Learning & Development — Expense up to $1,000/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 spouse/kids) — no weird loopholes, just care that works

  • Life & Disability insurance — Employer-paid short-term disability, long-term disability, and life insurance — coverage for life's curveballs

  • Supplemental options — Optional accident, critical illness, hospital indemnity, and voluntary life insurance for extra peace of mind

  • Doctegrity telehealth — Talk to a doctor from your couch

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

  • Pre-tax benefits — Access to FSAs and commuter benefits (US-only) to help your wallet out a bit

  • Pet insurance — Because fur babies are family too

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

Interview Process
  1. Application Review — Send us your stuff + a quick note on why this excites you. Show us what you've shipped — production systems, papers that became products, teams you've built. We care about impact, not pedigree.

  2. Technical Deep Dive (~75 min) — Go deep on your research and engineering work: architecture decisions, production tradeoffs, and results at scale. We'll explore a live problem — how you'd approach a core search/IR challenge at Firecrawl. We're looking for depth of understanding, production instincts, and the ability to connect research to business impact.

  3. Team & Leadership Interview (~45 min) — How you've built and led research teams. We'll dig into hiring decisions you've made, how you set direction, and how you create an environment where great researchers do their best work.

  4. Founder Chat (~30 min) — Culture, pace, ownership, and how you like to work. Time for your questions too.

  5. Paid Work Trial (1–2 weeks) — Test drive the real thing: tackle a real research problem with production implications. We'll evaluate on technical depth, speed, and how your work connects to the product.

  6. Decision — We move fast after the trial.

If you want to build the research team that gives Firecrawl an unfair technical advantage — and you're not afraid to ship your own code while you do it — this is your shot.

👉 Apply now and let's push the frontier. 🔬

Top Skills

Information Retrieval
Machine Learning
Ranking
Search
HQ

Firecrawl San Francisco, California, USA Office

San Francisco, CA, United States

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