- Страна
- США
- Зарплата
- 204 000 $ – 255 000 $
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Staff Software Engineer, Communication Products
Престижная компания, высокая заработная плата и возможность работать над передовыми ML-технологиями в глобальном масштабе. Удаленный формат работы в США и сильный социальный пакет делают вакансию исключительно привлекательной для опытных инженеров.
Сложность вакансии
Роль уровня Staff в компании уровня Tier-1 требует не только выдающихся технических навыков в области ML и распределенных систем, но и способности управлять сложными кросс-функциональными проектами. Высокие требования к опыту (9+ лет) и глубокая экспертиза в архитектуре делают прохождение отбора крайне сложным.
Анализ зарплаты
Указанный диапазон ($204k - $255k) является базовым окладом. Для уровня Staff в BigTech компаниях США это соответствует рынку, однако совокупный доход (TC) с учетом акций (RSU) и бонусов обычно значительно выше и может достигать $400k-$550k.
Сопроводительное письмо
I am writing to express my strong interest in the Staff Software Engineer position for Communication Products at Airbnb. With over nine years of experience in building high-scale distributed systems and a proven track record of integrating machine learning into production environments, I am excited by the opportunity to lead the technical vision for ML-powered messaging features. My background in architecting real-time messaging stacks and my familiarity with LLM-based product features align perfectly with your mission to build a first-class, intelligent messaging experience.
In my previous roles, I have successfully bridged the gap between ML research and product engineering, delivering scalable solutions for content moderation and conversational assistance. I am particularly drawn to Airbnb's commitment to fostering authentic connections and believe my expertise in NLP/NLU and event-driven architectures will help raise the engineering bar within your Communications organization. I look forward to the possibility of contributing to a team that values innovation, reliability, and a seamless user experience.
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Описание вакансии
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:
Messaging is a critical component in building connections with our users. Our mission as the Communication Products team is to build a first-class messaging experience at Airbnb, bringing together guests and hosts across the world. We are investing heavily in machine learning to make these conversations smarter, safer, and more productive. As a staff software engineer on this team, you'll lead the technical vision for ML-powered messaging features: architecting and delivering intelligent capabilities end-to-end, partnering deeply with ML and product teams, and raising the engineering bar across the organization.
The Difference You Will Make:
As a Staff Engineer on the team, you will define and drive the technical strategy for integrating ML capabilities into Airbnb's messaging products, including smart replies, message classification, content moderation, translation, and conversational assistance. You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration. In addition, you will help drive key technical deliverables for the larger Communications organization.
A Typical Day:
- Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability
- Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions
- Partner with ML, data science, and product teams to identify high-value opportunities, establish evaluation criteria, and close the gap between offline model performance and production impact
- Collaborate with other engineers and cross-functional partners across Messaging, Trust & Safety, Localization, and Platform organizations to align on long-term technical solutions
- Mentor, guide, advocate, and support the career growth of individual contributors
- Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation
Your Expertise:
- 9+ years of relevant engineering hands-on work experience
- Bachelors, Masters, or PhD in CS or related field
- Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring
- Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications
- Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding
- Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering
- Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution
- Experience operating distributed, real-time systems at scale with high reliability requirements
- Experience with real-time messaging systems or event-driven architectures
- Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference platforms)
- Prior work on trust & safety, content moderation, or internationalization in a messaging context
- Experience with LLM-based product features, including prompt engineering, retrieval-augmented generation, or fine-tuning
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.
Pay Range
$204,000—$255,000 USD
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Навыки
- Machine Learning
- NLP
- NLU
- Large Language Models
- Distributed Systems
- Architecture
- Scalability
- A/B Testing
- Observability
- Event-Driven Architecture
- Prompt Engineering
- Retrieval-Augmented Generation
Возможные вопросы на собеседовании
Для позиции Staff важно понимать, как кандидат проектирует системы, способные обрабатывать миллиарды сообщений с минимальной задержкой.
Как бы вы спроектировали архитектуру системы обмена сообщениями, которая должна поддерживать ML-инференс в реальном времени (например, для модерации контента) без значительного увеличения задержки (latency)?
Вакансия подразумевает тесную работу с ML-командами. Важно уметь оценивать эффективность моделей в реальном продукте.
Опишите ваш подход к сокращению разрыва между офлайн-метриками модели и её реальным влиянием на продукт (production impact). Как вы выстраиваете процесс онлайн-оценки?
Роль требует лидерства и влияния на другие команды.
Расскажите о случае, когда вам нужно было внедрить новый инженерный стандарт или технологию в нескольких командах. С какими трудностями вы столкнулись и как их преодолели?
Airbnb активно внедряет LLM. Кандидат должен понимать специфику работы с ними.
Какие основные проблемы вы видите при внедрении функций на базе LLM (например, умные ответы) в продукт с высокой нагрузкой, и как бы вы решали вопросы стоимости и галлюцинаций?
Staff-инженер должен уметь находить баланс между скоростью разработки и надежностью системы.
Как вы принимаете решение о том, когда стоит инвестировать в создание собственной инфраструктуры (например, Feature Store), а когда использовать готовые решения или временные костыли?
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- Страна
- США
- Зарплата
- 204 000 $ – 255 000 $