高级机器学习工程师，信任
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Senior Machine Learning Engineer, TrustAirbnb · San Francisco, CA
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。
为什么值得关注？
发现指数 42/100，仅依据与该职位一起存储的证据计算。
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分数构成
- 时效性 （随职位发布时间变化）+18
- 雇主官方来源+15
- 稀有职位+1
- 公司来源健康度+8
该职位未包含：已披露薪资、远程职位、提及签证担保、提及搬迁、未出现在监控的职位板上。
这些理由来自雇主自己的职位描述与我们核实过的来源检查结果。除了已存储的信号之外，我们不做任何推测。
职位描述
机器翻译Airbnb 诞生于 2007 年，当时两位房东在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，房东们提供独特的住宿和体验，让房客能够以更真实的方式与社区建立联系。
你将加入的社区：
Airbnb 的每个人都会思考信任问题，但我们的团队每天都在为此殚精竭虑。信任的核心是安全，因此我们投入大量时间和精力来保障社区安全。信任团队负责开发相关技术，帮助保护我们的社区和平台免受欺诈，同时确保我们的房东、房客、房源和体验达到我们的高标准。我们持续努力打击线上欺诈（例如金钱损失、账户被盗、消息中的垃圾信息和诈骗、虚假房源等）以及线下欺诈（盗窃、财产损失、人身安全等）。我们还负责用户入驻和筛查，并思考身份和声誉等复杂议题，以确保与 Airbnb 的每一次互动都有助于建立对我们和我们社区的信任。
信任前沿 AI 团队是信任领域新技术被发明和验证的地方。我们为关键任务的信任与安全问构建专用模型，开发可自动化信任决策的 AI 智能体和智能体能力，并创建基准和评估框架，以在这些智能体承担更多自主权时保持决策质量。我们在答案尚不明确时就开始研究问题——与合作伙伴团队一起制作原型、实验和迭代，直到解决方案在真实业务和顶线指标上证明自身价值。
你将与才华横溢的产品经理、数据科学家、软件工程师、欺诈情报和运营团队并肩工作。你们将共同设计和构建 ML 解决方案，对用户信任、业务成功和全球 Airbnb 社区产生直接而有意义的影响。
你将带来的不同：
作为信任前沿 AI 团队的高级机器学习工程师，你将积极贡献代码和想法，塑造保护数百万 Airbnb 用户的下一代 AI 系统。你将端到端地负责并交付 ML 项目，从界定模糊问题、制作解决方案原型，到训练模型并将其产品化，再到与一线团队一起证明其对顶线指标的影响。
你将从事跨多种防御的滥用行为检测、自主做出信任决策的 AI 智能体，以及使这些决策值得信赖的评估和基准工作。这些工作大多处于早期阶段：你将帮助决定构建什么，而不仅仅是如何构建，并推动其实现对平台可衡量的影响。
典型的一天：
• 与产品经理、数据科学家和一线防御团队合作，为尚无成熟方法的问题界定并制作 ML 和智能体解决方案原型。
• 为批处理和实时用例设计、构建并产品化端到端机器学习流水线——包括特征工程、模型训练、评估和部署。
• 构建并改进可跨多种防御泛化的滥用行为检测。
• 设计、上线并迭代可自动化信任决策的 AI 智能体，包括编排、工具接口，以及随着自主性提高而保持质量稳定的护栏。
• 构建基准、评估框架和埋点，使我们能够客观衡量智能体和模型决策质量，并用它们推动真正的改进。
• 为信任与安全用例开发专用模型，并使用 LLM 和 AI 智能体加速我们构建模型的方式。
• 编写、审查并交付干净、可测试的代码——无论是训练新模型、改进现有流水线，还是为可扩展性和可靠性优化功能。
• 处理大规模结构化和非结构化数据，持续改进面向 Airbnb 产品、业务和运营用例的 ML 模型。
• 与一线防御团队合作，通过实验和留出验证解决方案，并量化其对业务和运营指标的影响。
• 参与代码审查、设计讨论和跨团队协作，为高质量的 ML 工程文化做出贡献。
你的专长：
• 5-10 年应用机器学习行业经验，并有大规模构建和产品化模型的业绩记录。
• 1-2+ 年 LLM 和 GenAI 技术的实操经验，包括使用智能体框架、编排和评估进行构建。
• 扎实的 Python 编程能力（必需），并熟悉 Scala、Java 或同等语言。
• 对机器学习最佳实践有扎实理解——例如最小化训练/服务偏差、A/B 测试、特征工程、模型选择——以及梯度提升树、神经网络、Transformer 和深度学习等算法。
• 具有 TensorFlow、PyTorch 或同等 ML 框架和工具的经验。
• 具有数据工程和构建端到端 ML 流水线的经验，包括批处理和实时系统。
• 具有为 ML 或 LLM 系统设计评估方法论的经验——基准、真实标注、离线/在线指标、校准。
• 能适应模糊性并以行动为导向：你能够接手定义不清的问题，界定范围，快速制作原型，并推动其取得可衡量的成果。
• 接触过大型、高规模软件应用的架构模式（例如设计良好的 API、高吞吐数据流水线、高效算法）。
• 具有测试驱动开发、增量交付和部署实践的经验。
• 具有多模态模型（视觉、文档或语音）经验者优先。
• 接触过信任与风险领域（例如欺诈检测、异常检测、身份、账户完整性）者优先。
• 计算机科学/机器学习或相关领域的学士、硕士或博士学位。
你的工作地点：
该职位为美国 - 可远程。该职位可能包括偶尔在 Airbnb 办公室工作或参加异地活动，具体与你的经理商定。虽然该职位可远程，但你必须居住在 Airbnb, Inc. 拥有注册实体的州。点击此处查看最新的排除州列表。该列表持续变化，因此如果你居住的州在排除列表中，请再次与我们确认。如果你的职位由另一家 Airbnb 实体雇用，你的招聘人员将告知你可以从哪些州工作。
我们对包容与归属的承诺：
Airbnb 致力于与尽可能广泛的人才库合作。我们相信多元化的想法能够促进创新和参与，并使我们能够吸引具有创意领导力的人才，并开发最好的产品、服务和解决方案。鼓励所有符合条件的个人申请。
我们还努力提供对残障人士包容的申请和面试流程。如果你是残障候选人，并且需要合理便利才能提交申请，请通过以下方式联系我们：reasonableaccommodations@airbnb.com 。请包括你的全名、你申请的职位，以及协助你完成招聘流程所需的便利。
我们请求你仅在你因残障而无法完成我们的在线申请时才联系我们。 我们将如何照顾你：
我们的职位名称可能跨越多个职业级别。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，并可能在未来修改。该职位也可能有资格获得奖金、股权、福利和员工旅行积分。
薪资
$200,000 — $235,000 USD
合理便利：我们致力于在整个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，请在有人就某个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，从候选人那里骗取钱财或个人信息。对于 Airbnb 的招聘流程，有几件事始终属实：我们的空缺职位发布在 Airbnb 的职业页面上，网址为 careers.airbnb.com，我们的招聘人员只会从 @ 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询问你的社会安全号码、银行账户详细信息、护照或支付应用信息。我们也绝不会在面试过程中要求你支付费用、汇款、存入或兑现支票，或购买工作相关设备（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，如果你认为某个人并非真正隶属于 Airbnb，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。
查看雇主原文
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:
Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community.
The Trust Frontier AI team is where new AI technology for Trust gets invented and proven. We build specialized models for mission-critical trust and safety problems, develop the AI agents and agentic capabilities that automate trust decisions, and create the benchmarks and evaluation harnesses that keep decision quality high as those agents take on more autonomy. We work on problems before the answer is known — prototyping, experimenting, and iterating with our partner teams until a solution proves itself against real business and top line metrics.
You'll work side-by-side with talented product managers, data scientists, software engineers, fraud intelligence, and operations teams. Together, you'll design and build ML solutions that have direct, meaningful impact on user trust, business success, and the global Airbnb community.
The Difference You Will Make:
As a Senior Machine Learning Engineer on the Trust Frontier AI team, you will actively contribute code and ideas that shape the next generation of AI systems protecting millions of Airbnb users. You'll own and deliver ML projects end-to-end, from framing an ambiguous problem and prototyping a solution, to training and productionizing models, to proving impact on top line metrics with front line teams.
You'll work on abuse behavior detection that spans multiple defenses, on AI agents that make trust decisions autonomously, and on the evaluation and benchmarking work that makes those decisions trustworthy. Much of this work is early: you will help decide what to build, not only how to build it, and you'll see it through to measurable impact on the platform.
A Typical Day:
• Frame and prototype ML and agentic solutions for problems that do not yet have an established approach, in partnership with product managers, data scientists, and front line defense teams.
• Design, build, and productionize end-to-end Machine Learning pipelines — including feature engineering, model training, evaluation, and deployment — for both batch and real-time use cases.
• Build and improve abuse behavior detection that generalizes across defenses.
• Design, launch, and iterate on AI agents that automate trust decisions, including orchestration, tool interfaces, and the guardrails that hold quality steady as autonomy increases.
• Build benchmarks, evaluation harnesses, and instrumentation that let us measure agentic and model decision quality objectively, and use them to drive real improvements.
• Develop specialized models for trust and safety use cases, and use LLMs and AI agents to accelerate how we build models.
• Write, review, and ship clean, testable code — whether training a new model, improving an existing pipeline, or optimizing a feature for scalability and reliability.
• Work with large-scale structured and unstructured data to continuously improve ML models for Airbnb product, business, and operational use cases.
• Partner with front line defense teams to validate solutions through experiments and holdouts, and quantify their impact on business and operational metrics.
• Participate in code reviews, design discussions, and cross-team collaborations to contribute to a high-quality ML engineering culture.
Your Expertise:
• 5-10 years of industry experience in applied Machine Learning, with a track record of building and productionizing models at scale.
• 1-2+ years of hands-on experience with LLMs and GenAI technologies, including building with agentic frameworks, orchestration, and evaluation.
• Strong programming skills in Python (required) and familiarity with Scala, Java, or equivalent.
• Solid understanding of Machine Learning best practices — e.g., training/serving skew minimization, A/B testing, feature engineering, model selection — and algorithms such as gradient boosted trees, neural networks, transformers, and deep learning.
• Experience with ML frameworks and tooling such as TensorFlow, PyTorch, or equivalent.
• Experience with data engineering and building end-to-end ML pipelines, including both batch and real-time systems.
• Experience designing evaluation methodology for ML or LLM systems — benchmarks, ground truth, offline/online metrics, calibration.
• Comfort with ambiguity and a bias toward action: you can take a loosely defined problem, scope it, prototype quickly, and drive it to a measurable outcome.
• Exposure to architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high-volume data pipelines, efficient algorithms).
• Experience with test-driven development, incremental delivery, and deployment practices.
• Experience with multimodal models (vision, document, or speech) is a plus.
• Exposure to the Trust and Risk domain (e.g., fraud detection, anomaly detection, identity, account integrity) is a plus.
• A Bachelor's, Master's, or PhD in CS/ML or a related field.
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.
Our Commitment To Inclusion & Belonging:
Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.
We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com . Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.
We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application. 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
$200,000 — $235,000 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.