ClickUp
Machine Learning Engineer, Ranking & Retrieval
Remote role where the employee must remain based in a particular country.
United States only
Employer listed it 2 weeks ago · Added yesterday
Been open since 2 weeks ago, still being checked, but it has been live a while.
Salary
$200,000–$250,000
Location
United States only
Timezone
US East
Contract
Full-time
Experience
Mid
Category
Data
Published by the employer
Remote flexibility
Work from home
This is a remote role, but the employee must be based in United States. It is work from home rather than work from anywhere.
What the employer says
- Source listing states candidate location: "United States, Remote"
What Nomaders makes of it
- Residency required in United States
- Payroll and tax are likely handled in that country only
The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.
About the role
At ClickUp, we're building the future of work: the first truly converged AI workspace unifying tasks, docs, chat, calendar, and enterprise search, all supercharged by context-driven AI. We are an AI-native company. Every team member is expected to leverage AI daily, and we evaluate AI fluency as part of our hiring process. Join us and help redefine what's possible. 🚀
Machine Learning Engineer, Ranking & Retrieval
ClickUp is seeking an experienced Machine Learning Engineer to join our Search team. You'll own the ML systems that power search relevance for millions of users and ground our AI in the right context.
Your Impact at ClickUp
You'll own the full ML lifecycle for ranking and retrieval, from training through deployment and production serving. Our search indexes large-scale, user-generated content across a multi-tenant platform where permissions-aware retrieval is critical. You'll build the systems that decide what surfaces first.
Core 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
Technical 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
Preferred Qualifications
Permission-aware retrieval and multi-tenancy experience
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
Benefits
No benefits package published with this listing. Ask about it at first interview.
How to apply
- 1Check the flexibility label above, work from home, matches where you plan to live and work.
- 2Tailor your CV to the role at ClickUp, mentioning your remote working experience and working hours (US East).
- 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.
Found 1d ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.
Listing sourced from Company boards.
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