高级资深机器学习工程师，数据与评估
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Senior Staff Machine Learning Engineer, Data & EvalAirbnb · 美国
职位信息来自雇主公开的招聘页面。申请前请务必在雇主官网核实详情。
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职位描述
机器翻译Airbnb 诞生于 2007 年，当时两位房东在他们旧金山的家中接待了三位房客，此后已发展到超过 500 万名房东，在全球几乎每个国家接待了超过 20 亿人次房客入住。每天，房东们提供独特的房源和体验，让房客能够以更真实的方式与社区建立联系。
你将加入的团队：
AI 和 ML 是 Airbnb 产品的核心。从信任到支付，从客户服务到市场营销，我们都依赖 ML 来确保房客和房东在 Airbnb 获得尽可能最佳的体验。
核心 ML 团队负责通过采用生成式 AI 技术来推动 Airbnb Assistance Engineering 计划，以实现智能、可扩展且卓越的服务体验。该团队开发和增强 AI 模型、ML 服务和工具，包括 LLM 微调与优化、RAG/Search、LLM 评估与测试自动化、基于反馈的学习，以及适用于 Airbnb 各类应用的防护栏。
Airbnb 数据的丰富性、其市场的复杂性以及我们产品固有的多样性，意味着我们需要以最先进的 AI 实践来运作。我们致力于长期创新以解决复杂问题，为此我们需要经验丰富的 ML
你将带来的不同：
在这个 Senior Staff Machine Learning Engineering 职位中，你将设定技术方向，并主导 ML 评估以及驱动 Airbnb Assistance Engineering（例如辅助代理、问题解决和工具）的端到端数据飞轮的执行。你的工作将定义我们如何衡量质量、如何将反馈转化为学习信号，以及如何安全高效地持续改进模型和产品。你将与产品、工程、设计和运营紧密合作，构建可信、可扩展且可执行的评估系统——将离线指标与线上结果连接起来。
典型的一天：
• 为 GenAI 系统定义评估策略和成功指标，使离线评估与线上业务和客户体验结果保持一致。
• 构建并扩展评估框架（黄金集、合成数据、自动化回归、基于评分标准的评分、在适当情况下使用 LLM-as-judge），并对偏差、漂移和可靠性进行强有力的控制。
• 设计数据飞轮：埋点、反馈收集、数据质量检查、标注策略、数据集版本管理和治理，以支持持续改进。
• 主导跨产品、运营和工程的质量计划，推动各方明确“好”的标准以及团队如何根据评估结果采取行动。
• 开发并将数据集创建、模型监控、大规模评估和持续测试（部署前和部署后）的流水线投入生产。
• 推动评估和数据基础设施的技术决策与架构，平衡速度、严谨性、成本和安全性。
任职要求
• 教育背景：计算机科学、数学、统计学或相关技术领域的博士学位（或同等实践经验）。
• 行业经验：10 年以上端到端构建、测试和交付 ML/AI 系统的经验；其中包括 2 年以上在生产环境中使用 GenAI/LLM 系统的经验。
• 领导经验：5 年以上作为资深 IC 主导大型、模糊的技术计划的经验，影响跨团队的路线图和工程/科学方向。
• 技术能力： • 在评估方法方面拥有深厚专业知识（离线/线上对齐、指标设计、人在环评估、A/B 测试、功效分析、回归测试）。
• 具备 GenAI 系统的实操经验，包括编排、检索、工具调用、记忆等。
• 具备构建数据流水线和质量系统的经验（标注工作流、数据集整理、版本管理、监控和治理）。
• 扎实的 ML 基础知识和最佳实践（模型选择、训练/服务、监控、可靠性和模型生命周期管理）。
• 客户支持系统：具备将 ML/AI 应用于客户支持工作流（例如代理辅助、分类/路由、解决方案推荐、QA）的经验。
• 大规模基础设施与质量：具备构建稳健评估平台的经验，用于代理行为验证、安全/防护栏和持续改进。
• 应用 AI 的敏捷实践：具备将评估和数据飞轮工作从孵化推进到生产的可靠能力，在保持科学严谨性的同时快速迭代。
你的工作地点：
该职位为美国 - 可远程。根据与你的经理商定，该职位可能偶尔需要在 Airbnb 办公室工作或参加异地活动。虽然该职位可远程，但你必须居住在 Airbnb, Inc. 已注册实体所在的州。点击此处查看最新的排除州列表。该列表持续更新，因此如果你所在的州在排除列表中，请再次与我们确认。如果你的职位受雇于另一家 Airbnb 实体，你的招聘人员将告知你可以从哪些州工作。 我们将如何照顾你：
我们的职位名称可能跨越多个职级。实际基本工资取决于许多因素，例如：培训、可迁移技能、工作经验、业务需求和市场需求。基本工资范围可能会发生变化，并可能在未来进行修改。该职位还可能符合奖金、股权、福利和员工旅行抵用金的资格。
薪资
$244,000 — $305,000 USD
合理便利：我们致力于在招聘过程中为残障申请人提供合理便利。如果你需要帮助或便利，请在有人就职位联系你时告知你的招聘人员。
关于招聘诈骗的说明：诈骗者有时会冒充 Airbnb 招聘人员，从候选人处骗取钱财或个人信息。以下一些事项在 Airbnb 的招聘流程中始终属实：我们的空缺职位发布在 Airbnb 的职业页面 careers.airbnb.com 上，我们的招聘人员仅通过 @ airbnb.com 或 @ ext.airbnb.com 电子邮件地址联系。我们的招聘人员在你面试期间绝不会索要你的社会安全号码、银行账户信息、护照或支付应用信息。我们也绝不会要求你在面试过程中支付费用、汇款、存入或兑现支票，或购买与工作相关的设备（例如公司笔记本电脑）。我们鼓励候选人对此类招聘诈骗保持警惕，如果你不相信某个人确实与 Airbnb 有关联，请不要分享敏感信息。
以上内容由机器翻译自动生成，可能存在错误；投递前请以雇主原文为准。
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职位描述
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.
The Community You Will Join:
AI and ML are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing, we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb.
The Core ML team is responsible for driving Airbnb Assistance Engineering initiatives by adopting Generative AI technologies to enable an intelligent, scalable, and exceptional service experience. The team develops and enhances AI models, ML services, and tools including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning, and guardrails for a wide range of applications at Airbnb.
The richness of Airbnb's data, the complexity of its marketplace, and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to long-term innovation to solve complex problems, and to do that we need experienced ML
The Difference You Will Make:
In this Senior Staff Machine Learning Engineering role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering Airbnb Assistance Engineering (e.g., assistive agents, issue resolution, and tooling). Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently. You will partner closely with product, engineering, design, operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes.
A Typical Day:
• Define evaluation strategy and success metrics for GenAI systems, aligning offline evaluation with online business and customer experience outcomes.
• Build and scale evaluation frameworks (golden sets, synthetic data, automated regressions, rubric-based grading, LLM-as-judge where appropriate) with strong controls for bias, drift, and reliability.
• Design the data flywheel : instrumentation, feedback collection, data quality checks, labeling strategy, dataset versioning, and governance to support continuous improvement.
• Lead cross-functional quality initiatives across product, ops, and engineering, driving clarity on what “good” looks like and how teams act on evaluation results.
• Develop and productionize pipelines for dataset creation, model monitoring, evaluation-at-scale, and continuous testing (pre-deploy and post-deploy).
• Drive technical decisions and architecture for evaluation and data infrastructure, balancing speed, rigor, cost, and safety.
任职要求
• Educational Background : PhD in Computer Science, Mathematics, Statistics, or related technical field (or equivalent practical experience).
• Industry Experience : 10+ years building, testing, and shipping ML/AI systems end-to-end; including 2+ years of experience with GenAI/LLM systems in production.
• Leadership Experience : 5+ years leading large, ambiguous technical initiatives as a senior IC, influencing roadmap and engineering/science direction across teams.
• Technical Proficiency : • Deep expertise in evaluation methodology (offline/online alignment, metric design, human-in-the-loop evaluation, A/B testing, power analysis, regression testing).
• Hands-on experience with GenAI systems, including orchestration, retrieval, tool calling, memory, etc.
• Experience building data pipelines and quality systems (labeling workflows, dataset curation, versioning, monitoring, and governance).
• Solid ML fundamentals and best practices (model selection, training/serving, monitoring, reliability, and model lifecycle management).
• Customer Support Systems : Experience applying ML/AI to customer support workflows (e.g., agent assist, classification/routing, resolution recommendation, QA).
• Infrastructure & Quality at Scale : Experience building robust evaluation platforms for agent behavior validation, safety/guardrails, and continuous improvement.
• Agile Practice for Applied AI : Proven ability to take evaluation and data flywheel work from incubation to production, iterating quickly while maintaining scientific rigor.
Your Location:
This position is US - Remote Eligible. The role may include occasional work at an Airbnb office or attendance at offsites, as agreed to with your manager. While the position is Remote Eligible, you must live in a state where Airbnb, Inc. has a registered entity. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from. How We'll Take Care of You:
Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.
薪资
$244,000 — $305,000 USD
Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role.
A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @ airbnb.com or @ ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing. We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.