Machine Learning Engineer

Responsibilities

• Improve ranking and relevance for Firecrawl Search through feature engineering, model training, and production deployment.
• Build and tune learning-to-rank, query-understanding, recommendation, retrieval, and LLM-driven models.
• Extend machine learning across extraction quality, content classification, and evaluation of LLM-driven features.
• Analyze query logs and behavioral data to identify product strengths and failures.
• Build data pipelines that convert web-scale crawl and query data into training data and features.
• Collaborate with platform, search engineering, and cloud DevOps teams to deploy efficient production models.
• Design A/B testing frameworks and offline evaluation strategies.
• Define launch success metrics, run experiments, make evidence-based ship/no-ship decisions, and report post-launch performance.

Requirements

• 3+ years building machine-learning or data-heavy systems in production.
• Experience deploying, monitoring, retraining, and owning ML models after launch.
• Ranking or relevance-modeling experience, including learning-to-rank, recommendations, or search quality.
• Experience working with large-scale query logs, pipelines, and datasets.
• Production-quality programming skills, including Python, and ability to work in backend codebases.
• Experience designing and analyzing A/B tests.
• Clear communication of technical results and recommendations.

Nice to Have

• MLOps experience with MLflow, experiment tracking, model registries, or feature stores.
• Kubernetes experience.
• Experience building or standardizing experimentation frameworks.
• Experience with embedding models, vector retrieval, or LLM-based relevance evaluation.
• Experience evaluating LLM outputs at scale.
• Spark or similar large-scale data-processing experience.

Compensation & Benefits

• Salary: $210,000–$240,000 per year.
• Competitive equity.
• 15 days mandatory PTO, with additional time available by request.
• 12 weeks of fully paid parental leave.
• $100/month wellness stipend.
• Up to $1,000/year for learning and development.
• Team offsites and a three-month paid sabbatical after four years.
• Medical, dental, and vision coverage for US-based full-time employees.
• Employer-paid short-term disability, long-term disability, and life insurance.
• Optional supplemental insurance, telehealth, 401(k), FSAs, commuter benefits, and pet insurance.
• San Francisco HQ perks and an e-bike transportation loaner for SF-based employees.
• Paid work trial at a contractor rate.