机器学习工程师，排名与检索
Machine Learning Engineer, Ranking & Retrieval
在 ClickUp，我们正在打造未来的工作方式：首个真正融合 AI 的工作空间，将任务、文档、聊天、日历和企业搜索统一起来，所有功能都由以上下文驱动的 AI 提升。我们是一家以 AI 为核心的企业。每位团队成员都需要每天使用 AI，我们在招聘过程中会评估 AI 熟练程度。加入我们，一起重新定义可能。🚀
机器学习工程师，排序与检索
ClickUp 正在寻找一位经验丰富的机器学习工程师加入我们的搜索团队。你将负责支持数百万用户搜索相关性的机器学习系统，并为我们的 AI 提供正确的上下文基础。
你在 ClickUp 的影响
你将负责排序与检索的完整机器学习生命周期，从训练到部署和生产服务。我们的搜索系统处理大规模的用户生成内容，跨多租户平台，权限感知的检索至关重要。你将构建决定内容优先展示的系统。
核心职责
- 在生产环境中训练、部署并提供排序模型，负责完整的机器学习生命周期
- 构建排序特征、训练流水线和离线评估框架
- 设计并扩展结合词法和向量搜索的混合检索系统（包括 HNSW 和磁盘卸载）
- 在数十亿文档规模上运行嵌入推理
- 通过意图建模和查询扩展提升查询理解
- 构建尊重多租户边界的权限感知检索
- 创建评估和改进搜索质量的度量框架
- 与搜索基础设施、AI 和后端团队合作，将排序改进整合到整个平台中
技术要求
- 计算机科学、机器学习或相关领域的学士学位
- 5 年以上专注于排序、检索或信息检索的机器学习工程经验
- 有完整的机器学习生命周期经验：训练、部署和提供模型
- 有排序模型训练的实际经验：特征工程、流水线、离线评估
- 有构建混合（词法 + 向量）检索系统的经验
- 有在大规模运行嵌入推理的经验
- 强大的查询理解基础：意图建模、查询扩展
优先资格
- 有权限感知检索和多租户经验
- 有处理大规模用户生成内容的经验（非小规模或静态数据集）
- 有使用 OpenSearch 或 Elasticsearch 的实际经验
- 有分片、索引管理经验
查看英文原文
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
- 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
Join Our Mission
At ClickUp, we're committed to building the future of productivity software. As our Search Engineer, you'll play a crucial role in shaping the core functionality of our platform and driving our AI initiatives forward. Join us in our mission to make the world more productive!
#LI-REMOTE
Equal Opportunity Employer
ClickUp is an Equal Opportunity Employer, and qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, or national origin.
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Visa Sponsorship
Please note we are unable to sponsor or take over sponsorship of an employment visa for roles outside of engineering and product at this time. Sponsorship for engineering and product roles is not guaranteed, but is instead based on the business needs for that specific role at that time. Please reach out to the recruiter with any questions.
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