Staff Machine Learning Engineer - Policy & Safety

What You Will Do

• Build and scale machine learning systems for proactive content detection, classification, and pre-publish safety scanning
• Design and implement policy evaluation frameworks, including standardized datasets, offline and online metrics, and continuous improvement loops
• Develop multimodal models that combine text, audio, image, and video signals for safety and policy enforcement
• Architect feedback loops that turn human reviewer input into structured training data for continuous model improvement
• Translate regulatory requirements (e.g., precision/recall obligations, compliance reporting) into scalable ML system designs
• Partner with cross-functional teams across Trust & Safety, Legal, Public Affairs, and Product to deliver safe user experiences
• Drive technical direction in ambiguous problem spaces and contribute to long-term platform architecture
• Mentor and support other machine learning engineers, helping raise the bar across the team

Who You Are

• Experience building and shipping production-grade machine learning systems at scale
• Strong expertise in ML evaluation, including dataset design, metrics, and model performance monitoring
• Worked with multimodal machine learning systems across text, audio, image, or video domains
• Experienced with human-in-the-loop systems, active learning, or feedback-driven model improvement
• Comfortable translating complex requirements into technical solutions, including regulatory or policy constraints
• Experience working across teams and influencing technical direction in large-scale systems
• Comfortable navigating ambiguity and making thoughtful decisions that balance speed, quality, and risk
• Communicate clearly and collaborate effectively with both technical and non-technical stakeholders