Research Engineer — Reinforcement Learning

San Francisco, CA (Hybrid) OR Remote (Americas, UTC-3 to UTC-10)Remotefull-timemid

OtherResearch Engineer

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Quick Summary

Overview

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.

Key Responsibilities

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.

Requirements Summary

Builds their own training infra and reward pipelines. You don't wait for an ML platform team to set things up. You build the training loops, reward models, data pipelines, and evaluation frameworks yourself — because you understand that infra…

Technical Tools

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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.