Principal Machine Learning Engineer, Content Safety
Core
Define the 3-5 year technical strategy and architectural blueprint for massive-scale machine learning systems that proactively detect and mitigate violative user-generated content to ensure platform civility and safety.
Role type
Principal Machine Learning Engineer (Content Safety)
Builds
Massive-scale ML inference services, auto-labeling pipelines, and production systems for content moderation.
Domain
Internet platform safety, User-Generated Content (UGC) moderation, Computer Vision (CV), Vision-Language Models (VLMs)
Deliverable
production ML models
Required skills
Advanced ML architectures (CV, VLMs), scalable real-time ML inference, robust data pipeline architecture, transfer-learning, self-supervised learning, quantization, LoRA, distillation, backend integration, strategic roadmap planning, cross-functional leadership
Preferred skills
Experience with modern AI coding tools, ability to synthesize complex business goals into technical strategy, building consensus among diverse stakeholders
Technologies
Cursor, transfer-learning, self-supervised learning, quantization, LoRA, distillation
Responsibilities
Define and lead multi-year technical vision and architectural strategy for content safety ML solutions; collaborate with executive-level stakeholders to prioritize the ML roadmap; oversee adoption and deployment of innovative ML techniques; construct datasets from scratch and build auto-labeling pipelines; integrate ML work into the production stack and handle infrastructure complexity.
Seniority
Principal, strategy & mentorship
