Research Engineer — Reinforcement Learning

RESEARCH ENGINEER — REINFORCEMENT LEARNING

You'll bring reinforcement learning to Firecrawl's core product — building the training infrastructure, reward pipelines, and fine-tuning systems that make our models meaningfully better at extracting, understanding, and structuring web data. This isn't theoretical RL research. You'll build your own training infra, run fast experiments, ship models to production, and bridge the gap between classical RL approaches and modern LLM agent systems. If you care as much about training throughput as you do about reward design, this is the role.

Salary Range: $180,000–$290,000/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:

Equity Range: Up to 0.15%

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

Job Type: Full-Time

Experience: 3+ years in applied RL, ML engineering, or model training — with production systems

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 100k+ 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 superintelligence will use to gather data on the web. We ship fast and deep.

WHAT YOU'LL DO

Build training infrastructure and reward pipelines from scratch. Design and operate the systems that train and evaluate Firecrawl's models. You'll own the full loop — data collection, reward modeling, training runs, evaluation, and deployment. You build the infra yourself because you're the one who needs it to work.

Fine-tune models to achieve state-of-the-art results. Take foundat...