Staff Software Engineer, Communication & Connectivity
AirbnbUnited StatesPosted 24 February 2026
Job Description
<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>We connect Airbnb’s community with the right information, in the right place, at the right time. We tailor Messaging Notifications so hosts on Airbnb can streamline their operations, and travelers get just the information they need to enjoy their stay worry-free. Additionally, we are building new connections within our community to help enrich the experience of hosting traveling on Airbnb: easing the process of hosting, and adding meaning to our guest’s trips.</p>
<p>The data team utilizes industry-leading tools, builds scalable data systems and applies cutting-edge ML models to provide insights and empower all products in the Communication and Connectivity (CnC) organization.</p>
<p><strong>The Difference You Will Make:</strong></p>
<p>At CnC, data is foundational to our organization’s success.This role will lead key initiatives to design and build large-scale, distributed data systems - both batch and real-time processing. The data will power machine learning models and unlock new product features. You’ll be at the center of cross-functional collaboration, bridging backend, frontend/client, and machine learning engineering teams.</p>
<p>CnC is applying GenAI and large language models (LLMs) to power products that enhance the Airbnb experience in various surfaces including highly used ones like Messaging. We're building a robust ML platform to power our product ambitions.</p>
<p><strong>A Typical Day: </strong></p>
<ul>
<li>Shape the team’s long-term vision and roadmap in close collaboration with cross-functional partners across Airbnb</li>
<li>Build strong relationships with partner engineering teams, including backend, client, data science, analytics, and ML, to drive aligned and impactful outcomes</li>
<li>Design, develop, and maintain reliable, scalable data pipelines - both batch and real-time - that collect, process, and serve data from diverse sources across Airbnb</li>
<li>Implement robust offline and online feature building processes to enable faster production of ML products</li>
<li>Architect and build ML infra and optimize for performance, scalability, and cost-effectiveness</li>
<li>Mentor and develop engineers on the team, while also contributing to and influencing the broader data engineering community at Airbnb</li>
</ul>
<p><strong>Your Expertise:</strong></p>
<ul>
<li>9+ years of relevant industry experience with a Bachelor’s and/or Master’s degree in CS/EE, or equivalent experience, or 6+ years of experience with a PhD</li>
<li>Strong CS fundamentals, and knowledge of architecture and common design patterns </li>
<li>You’re passionate about being in a product-focused environment where everyone cares deeply about customer impact</li>
<li>You have experience of running data processing pipelines in production using distributed data processing frameworks like Apache Spark or Flink</li>
<li>Experience collaborating with client, backend, ml, analytics teams, product and business partners</li>
<li>Effectively work across team boundaries to establish overarching data architecture, data flow, and provide guidance to individual teams</li>
<li>Experience working on/with end-to-end Machine Learning products</li>
<li>Excellent communication skills, both written and verbal</li>
</ul>
<p><span style="color: #000000; font-family: arial, helvetica, sans-serif;"><strong>Your Location:</strong></span></p>
<p><span style="font-family: arial, helvetica, sans-serif; color: #000000;"><span style="font- ... (truncated, view full listing at source)
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