Machine Learning Engineer, Ranking & Retrieval

Location: Remote within the United States

Salary: $200,000–$250,000 annual compensation plus equity

Company

ClickUp develops an AI-native productivity workspace that unifies tasks, documents, chat, calendars, and enterprise search.

What you will do

• Own the full machine learning lifecycle for ranking and retrieval models, from training and deployment to production serving.
• Build ranker features, training pipelines, and offline evaluation frameworks.
• Design and scale hybrid lexical and vector retrieval, including HNSW with disk offloading.
• Run embedding inference at billions-of-documents scale and improve query understanding through intent modeling and query expansion.
• Build permissions-aware retrieval for a multi-tenant platform and create frameworks for measuring search quality.
• Collaborate with Search Infrastructure, AI, and backend teams to integrate ranking improvements.

Requirements

• Bachelor’s degree in Computer Science, Machine Learning, or a related field.
• 5+ years of machine learning engineering experience focused on ranking, retrieval, or information retrieval.
• Production experience owning model training, deployment, and serving across the full ML lifecycle.
• Hands-on experience with ranker model training, feature engineering, pipelines, and offline evaluation.
• Experience building hybrid lexical and vector retrieval systems and running embedding inference at large scale.
• Strong fundamentals in query understanding, including intent modeling and query expansion.

Nice to have

• Experience with permissions-aware retrieval, multi-tenancy, and large-scale user-generated content.
• Hands-on experience with OpenSearch or Elasticsearch, sharding, index management, and real-time ingestion.
• Background in NLP, semantic search, or agentic retrieval.
• Experience with TypeScript in backend systems.

Culture & Benefits

• Remote work within the United States.
• Equity, 401(k), health, dental, and vision insurance.
• Spending accounts, life and disability coverage, paid parental leave, and flexible paid time off.
• Employee assistance, wellness, and professional development stipends.
• AI fluency is evaluated during the hiring process, and daily AI usage is expected.

Hiring process

• AI fluency is assessed as part of the hiring process.