Machine Learning Engineer, Ranking & Retrieval

About the role

ClickUp is seeking an experienced Machine Learning Engineer to join its Search team, owning the ML systems that power search relevance for millions of users. You will be responsible for the full ML lifecycle for ranking and retrieval, ensuring the AI is grounded in the right context across a multi‑tenant platform.

Key responsibilities

• Train, deploy, and serve ranking models in production, managing the end‑to‑end 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.
• Develop 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.

Required profile

• Bachelor’s degree in Computer Science, Machine Learning, or a related field.
• 5+ years of ML engineering experience focused on ranking, retrieval, or information retrieval.
• Proven ownership of the full ML lifecycle: training, deploying, and serving models in production.
• Hands‑on experience building hybrid (lexical + vector) retrieval systems and running large‑scale embedding inference.

Required skills

• Hybrid search (lexical and vector) implementation, including HNSW.
• Embedding inference at large scale.
• Query intent modeling and query expansion techniques.
• OpenSearch or Elasticsearch, sharding, index management, and real‑time ingestion.
• TypeScript for backend development.
• Natural Language Processing, semantic search, and agentic retrieval.