Staff Software Engineer, Communication Products

<div class="content-intro"><p><span style="font-family: helvetica, arial, sans-serif; font-size: 12pt;">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.</span></p></div><p><strong>The Community You Will Join:</strong></p> <p>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.</p> <p><strong>The Difference You Will Make:</strong></p> <p>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.</p> <p><strong>A Typical Day: </strong></p> <ul> <li>Design, build, and operate the systems that serve ML models within the messaging stack, with a focus on latency, reliability, and scalability</li> <li>Write and review technical designs that solve large, open-ended problems at the intersection of ML and product engineering without clearly-known solutions</li> <li>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</li> <li>Collaborate with other engineers and cross-functional partners across Messaging, Trust Safety, Localization, and Platform organizations to align on long-term technical solutions</li> <li>Mentor, guide, advocate, and support the career growth of individual contributors</li> <li>Establish engineering standards for ML integration across the messaging surface, including feature flagging, A/B testing, observability, and graceful degradation</li> </ul> <p><strong>Your Expertise:</strong></p> <ul> <li>9+ years of relevant engineering hands-on work experience</li> <li>Bachelors, Masters, or PhD in CS or related field</li> <li>Demonstrated experience building and shipping ML-powered product features in production environments, including model serving, feature pipelines, online/offline evaluation, and monitoring</li> <li>Exceptional architecture abilities and experience with architectural patterns of large, high-scale applications</li> <li>Familiarity with NLP/NLU techniques and large language models, particularly as applied to messaging, conversational AI, or content understanding</li> <li>Shipped several large-scale projects with multiple dependencies across teams, specifically at the intersection of ML infrastructure and product engineering</li> <li>Technical leadership and strong communication skills with the ability to translate between ML research, product goals, and engineering execution</li> <li>Experience operating distributed, real-time systems at scale with high reliability requirements</li> <li>Experience with real-time messaging systems or event-driven architectures</li> <li>Familiarity with ML infrastructure at scale (e.g., feature stores, model registries, online inference ... (truncated, view full listing at source)