高级资深软件工程师，主机定价与设置
Senior Staff Software Engineer, Host Pricing & Settings
Airbnb 诞生于 2007 年，当时两位房东欢迎三位客人入住他们的旧金山住宅，如今已发展为超过 500 万房东，他们在全球几乎每个国家都接待了超过 20 亿次宾客到访。每天，房东们提供独特的住宿和体验，使宾客能够以更真实的方式与社区建立联系。
你将加入的团队：
Host Pricing & Settings 团队构建平台和工具，帮助房东运营业务——定价策略基于市场情报、可比房源和需求信号。我们与 Search、Listings、Tax 和 Payments 合作，确保我们的建议准确、及时且值得信赖。
每一条定价建议背后，是一个正在经历根本性重构的复杂 ML 系统。我们的目标：一个设计上保持一致的部署基础设施——特征来自集中式存储，模型组合在一个地方，按需提供回填功能，使得数据科学家和 MLE 能够在几天而不是几周内评估候选方案。
你将带来的改变：
作为高级技术个人贡献者，你将负责 Host Pricing 组织中从建模 → ML 部署 → API 接口的整个技术策略。尽管你处于我们最高级别的资深职位，但 Airbnb 所有个人贡献者都是软件工程师——你被期望亲自参与并编写代码。
- 定义模型从开发到生产过程中所遵循的架构和契约——特征存储设计、模型模式管理、在线/离线推理一致性以及多版本支持。
- 领导构建统一的部署栈，消除每个模型的定制实现，并为数据科学家提供从训练到生产的即插即用路径。
- 架构回填和评估基础设施，使建模团队能够在几天而不是几周内对历史数据进行生产推理模拟。
- 在建模和部署之间建立领域契约，使每个团队可以独立运作，拥有清晰且强制执行的接口。
典型的一天：
- 审查并改进 ML 部署架构——在特征流水线设计、模型组合和 API 接口上做出权衡决策。
- 编写和审查特征工程任务、特征存储配置和部署服务端点的代码。
- 与数据科学、MLE、MLI 和核心定价与可用性系统后端团队合作，定义 artifact
查看英文原文
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.
Preferred Qualifications:
- 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.