高级资深软件工程师，主机定价与设置
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Senior Staff Software Engineer, Host Pricing & SettingsAirbnb · Remote - USA
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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- 雇主官方来源+15
- 远程职位+8
- 稀有职位+1
- 公司来源健康度+8
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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：
房东定价与设置团队构建平台和工具，帮助房东经营业务——定价策略基于市场情报、可比房源和需求信号。我们与搜索、房源、税务和支付团队合作，确保我们的指导准确、及时且值得信赖。
每一个定价建议背后，都是一个正在经历根本性重构的复杂 ML 系统。我们的北极星：一个服务基础设施，使训练、推理和评估在设计上保持一致——特征来自集中式存储，模型组合集中在一处，回填可按需提供，让数据科学家和 MLE 能在几天内而非几周内评估候选模型。
你将带来的不同：
作为资深技术个人贡献者，你将负责房东定价组织内从建模 → ML 服务 → API 接口的完整技术战略。尽管你将处于我们最高资历级别之一，但 Airbnb 的所有个人贡献者都是软件工程师——你需要亲自动手并贡献代码。
• 定义模型从开发到生产的架构和契约——特征存储设计、模型 schema 管理、在线/离线推理一致性以及多版本支持。
• 主导统一服务栈的建设，消除每个模型的一次性实现，并为数据科学家提供从训练到生产的开箱即用路径。
• 设计回填和评估基础设施，使建模团队能够在几天内而非几周内基于历史数据模拟生产推理。
• 在建模与服务之间建立领域契约，使每个团队都能通过清晰、强制的接口独立推进。
典型的一天：
• 审查并演进 ML 服务架构——在特征管道设计、模型组合和 API 接口方面做出权衡决策。
• 为特征工程作业、特征存储配置和服务服务端点编写并审查代码。
• 与数据科学、MLE、MLI 以及核心定价与可用性系统 BE 团队合作，定义工件交接和集成契约。
• 推动房东定价与设置组织的里程碑规划，安排工作顺序以增量交付价值。
• 通过设计评审和在最困难基础设施问题上的动手结对来指导工程师。
你的专长：
• 12 年以上后端或平台工程经验，并拥有构建生产 ML 系统或数据密集型基础设施的大量经验。
• 具备 Java、Kotlin、Scala 和/或 Python 的强编程能力。
• 深入理解 ML 系统设计：特征存储、训练/服务一致性、模型版本管理以及在线/离线推理管道。
• 具备大规模批处理和实时数据管道经验（Spark、Airflow、Kafka 或同等技术），包括回填的时间点正确性。
• 精通大型、高规模应用的架构模式——设计良好的 API、高效的数据契约、多租户服务基础设施。
• 已证明有能力领导跨越 ML 和平台工程的跨团队技术计划。
任职要求
• 特征存储深度：具备 Chronon、Tecton、Feast 或同等技术的生产经验——包括在线/离线一致性和回填自动化。
• 模型服务基础设施：具备模型 schema 管理、多版本支持和模型组合框架经验。
• 领域契约设计：有定义并强制执行 ML 建模、MLI、服务团队和/或产品界面之间技术契约的过往记录。
• 评估速度：在提升 ML 团队评估候选模型并发布到生产的速度方面有可衡量的影响。
你的地点：
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。如果你的职位由另一个 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促进创新和参与，并使我们能够吸引具有创造力的领导者，并开发最好的产品、服务和解决方案。鼓励所有合格个人申请。
我们也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，并且在提交申请时需要合理便利，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。
合理便利：我们致力于在招聘流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，从候选人那里获取金钱或个人信息。对于 Airbnb 的招聘流程，有几件事始终成立：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、银行账户详情、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，如果你不相信某个人确实隶属于 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。
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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:
The Host Pricing & Settings team builds the platform and tools that help hosts run their business — with pricing strategies informed by market intelligence, comparable listings, and demand signals. We partner with Search, Listings, Tax, and Payments to ensure our guidance is accurate, timely, and trusted.
Behind every pricing recommendation is a sophisticated ML system undergoing a fundamental rearchitecture. Our north star: a serving infrastructure where training, inference, and evaluation are consistent by design — features from a centralized store, model composition in one place, and backfills available on demand so data scientists and MLEs can evaluate candidates in days, not weeks.
The Difference You Will Make:
As a senior technical individual contributor, you will own the technical strategy for the full Modeling → ML Serving → API interface across the Host Pricing org. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers — you are expected to be hands-on and contribute code.
• Define the architecture and contracts governing how models move from development to production — feature store design, model schema management, online/offline inference consistency, and multi-version support.
• Lead the buildout of a unified serving stack that eliminates per-model one-off implementations and gives data scientists a turnkey path from training to production.
• Architect backfill and evaluation infrastructure so the modeling team can simulate production inference over historical data in days, not weeks.
• Establish domain contracts between Modeling and Serving so each team can move independently with clear, enforced interfaces.
A Typical Day:
• Review and evolve the ML serving architecture — making tradeoff calls on feature pipeline design, model composition, and API interfaces.
• Write and review code for feature engineering jobs, feature store configurations, and serving service endpoints.
• Partner with Data Science, MLE, MLI and core Pricing & Availability systems BE teams to define artifact handoffs and integration contracts.
• Drive milestone planning across the Host Pricing & Settings org, sequencing work to deliver value incrementally.
• Mentor engineers through design reviews and hands-on pairing on the hardest infrastructure problems.
Your Expertise:
• 12+ years in backend or platform engineering, with substantial experience building production ML systems or data-intensive infrastructure.
• Strong programming skills in Java, Kotlin, Scala, and/or Python.
• Deep understanding of ML systems design: feature stores, training/serving consistency, model versioning, and online/offline inference pipelines.
• Experience with high-scale batch and real-time data pipelines (Spark, Airflow, Kafka, or equivalent), including point-in-time correctness for backfills.
• Expertise with architectural patterns of large, high-scale applications — well-designed APIs, efficient data contracts, multi-tenant serving infrastructure.
• Proven ability to lead cross-team technical initiatives spanning ML and platform engineering.
任职要求
• Feature Store Depth: Production experience with Chronon, Tecton, Feast, or equivalent — including online/offline consistency and backfill automation.
• Model Serving Infrastructure: Experience with model schema management, multi-version support, and model composition frameworks.
• Domain Contract Design: Track record defining and enforcing technical contracts between ML modeling, MLI, serving teams and/or product surfaces.
• Evaluation Velocity: Measurable impact improving the speed at which ML teams evaluate candidate models and ship to production.
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. 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.
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.