Machine Learning Engineer

Responsibilities

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

Requirements

• At least 3 years of experience building ML or data-heavy systems in production.
• Experience shipping, deploying, monitoring, and retraining machine learning models after launch.
• Hands-on ranking or relevance-modeling experience, such as learning-to-rank, recommendations, or search quality.
• Experience working with large query logs, data pipelines, and datasets that do not fit in memory.
• Production-quality coding ability in Python and the ability to work within a backend codebase.
• Experience designing and analyzing A/B tests and evaluating whether measured improvements are meaningful.
• Ability to communicate shipped work, measured outcomes, and next steps clearly.
• Preferred: MLOps experience with experiment tracking, model registries, or feature stores.
• Preferred: Kubernetes, experimentation-framework development, embedding models, vector retrieval, LLM-based relevance evaluation, large-scale LLM output evaluation, or Spark experience.

Benefits

• Hybrid role based in San Francisco with on-site work required.
• Full-time employment with medical, dental, and vision coverage for US-based employees.
• 15 days of mandatory PTO, with additional time encouraged after 24 days, excluding holidays.
• 12 weeks of fully paid parental leave for all parents.
• $100 monthly wellness stipend.
• Up to $1,000 per year for professional learning and development.
• Team offsites and a three-month paid sabbatical after four years.
• Employer-paid short-term disability, long-term disability, and life insurance, plus optional supplemental insurance.
• 401(k), FSA, commuter benefits, pet insurance, and Doctegrity telehealth for eligible US-based employees.
• San Francisco employees receive office snacks, drinks, team lunches, and a loaner electric bike.
• Paid 1–2 week work trial at a contractor rate, remote-friendly and flexible around current commitments.