Machine Learning Engineer, Ranking & Retrieval

Job not on LinkedIn

🔥 24 minutes ago

🇺🇸 United States – Remote

💵 $200k - $250k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

🤖 Machine Learning Engineer

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ClickUp

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

Founded 2017

☁️ SaaS

⚡ Productivity

🏢 Enterprise

💰 $400M Series C - ClickUp on 2021-10

SaaS • Productivity • Enterprise

ClickUp is a cloud-based SaaS work management and productivity platform that consolidates projects, docs, chat, time tracking, automations and AI-driven "Super Agents" into a single workspace. It helps teams and enterprises streamline workflows, replace fragmented software stacks, and boost productivity with integrations, customizable agents/workflows, and enterprise-grade security and compliance.

📋 Description

• Own the full ML lifecycle for ranking and retrieval, from training through deployment and production serving • 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 • 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

🏖️ Benefits

• Equity • 401k • Health, Dental, and Vision insurance • Spending accounts • Life & Disability • Paid parental leave • Flexible paid time off • Enhanced employee assistance program • Employee wellness stipend • Professional development stipend