Machine Learning Engineer Safety

You will own machine learning models and production infrastructure for safety and abuse detection. You will improve detection accuracy, coverage, latency, and scalability; integrate systems with core infrastructure; assess third-party tools; and introduce relevant safety techniques.

Responsibilities

• Design, build, and maintain machine learning models and infrastructure for safety and abuse detection
• Improve the accuracy, coverage, latency, and scalability of detection pipelines
• Integrate safety systems with core platform infrastructure
• Evaluate and integrate third-party safety tooling and vendor models
• Apply new machine learning safety techniques and infrastructure patterns

Requirements

• Hands-on experience in trust and safety, content moderation, or abuse and detection systems
• End-to-end engineering ability across machine learning and production infrastructure
• Ability to own ambiguous, high-stakes problems
• Based in San Francisco

Benefits

• Equity
• Relocation assistance to San Francisco
• Health, dental, and vision insurance
• Regular team events and offsites