Machine Learning Engineer, Ranking & Retrieval

ClickUp is building an AI-native workspace that unifies productivity tools and enterprise search. The Machine Learning Engineer will own the machine learning lifecycle for ranking and retrieval, including model training, deployment, production serving, hybrid search, embedding inference, query understanding, and permissions-aware retrieval at scale.

Responsibilities:

• 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

Requirements:

• • 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, and serving models in production
• • Hands-on ranker model training: feature engineering, pipelines, offline evaluation
• • Experience building hybrid (lexical + vector) retrieval systems
• • Experience running embedding inference at large scale
• • Strong query understanding fundamentals: intent modeling, query expansion
• • Permission-aware retrieval and multi-tenancy experience
• • Indexing large-scale user-generated content (not small or static datasets)
• • Hands-on experience with OpenSearch or Elasticsearch
• • Sharding, index management, and real-time ingestion at scale
• • Background in NLP, semantic search, or agentic retrieval
• • Experience with TypeScript in backend systems