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ClickUp is seeking an experienced Machine Learning Engineer to join the Search team, owning the ML systems that power search relevance for millions of users. You will own the full ML lifecycle for ranking and retrieval—from training through deployment and production serving—for a multi-tenant platform where permissions-aware retrieval is critical.
Core responsibilities include training, deploying, and serving ranking models in production; building ranker features, training pipelines, and offline evaluation frameworks; designing and scaling hybrid retrieval systems combining lexical and vector search (including HNSW with disk offloading); running embedding inference at billions-of-documents scale; improving query understanding through intent modeling and query expansion; building permissions-aware retrieval that respects multi-tenant boundaries; creating measurement frameworks to evaluate and improve search quality; and collaborating with Search Infrastructure, AI, and backend teams to integrate ranking improvements across the platform.
Required qualifications include a Bachelor's degree in Computer Science, Machine Learning, or related field; 5+ years of ML engineering experience focused on ranking, retrieval, or information retrieval; proven full ML lifecycle ownership (training, deploying, serving models in production); hands-on ranker model training with feature engineering, pipelines, and offline evaluation; experience building hybrid retrieval systems; experience running embedding inference at large scale; and strong query understanding fundamentals including intent modeling and query expansion.
Preferred qualifications include permission-aware retrieval and multi-tenancy experience; indexing large-scale user-generated content; hands-on experience with OpenSearch or Elasticsearch; sharding, index management, and real-time ingestion at scale; background in NLP, semantic search, or agentic retrieval; and TypeScript experience in backend systems.
ClickUp is an AI-native company where every team member is expected to leverage AI daily. You'll play a crucial role in shaping the core search functionality of a converged AI workspace platform unifying tasks, docs, chat, calendar, and enterprise search.
