Machine Learning Engineer, Ranking & Retrieval

Responsibilities

• You'll own the full ML lifecycle for ranking and retrieval, from training through deployment and production serving. Our search indexes large-scale, user-generated content across a multi-tenant platform where permissions-aware retrieval is critical. You'll build the systems that decide what surfaces first.
• Train, deploy, and serve ranking models in production, owning the full ML lifecycle
• Build ranker features, training pipelines, and offline evaluation frameworks
• Design and scale hybrid retrieval combining lexical and vector search (including HNSW with disk offloading)
• Run embedding inference at billions-of-documents scale
• Improve query understanding through intent modeling and query expansion
• Build permissions-aware retrieval that respects multi-tenant boundaries
• Create measurement frameworks to evaluate and improve search quality
• Collaborate with Search Infrastructure, AI, and backend teams to integrate ranking improvements across the platform

Languages