Role overviewAirbnb’s Growth Platform team’s vision is to drive long term sustainable growth for the Airbnb community. The mission is to build a best-in-class agentic system and capabilities to support the growth of all Airbnb products, current and future—delivering highly personalized and relevant content and product experiences both on and off the Airbnb platform. The north star is full autonomy, where AI identifies opportunities, creates campaigns, personalizes experiences, and optimizes outcomes with minimal human intervention, with human-in-the-loop controls at every stage to ensure brand safety, quality, and compliance.The Difference You Will MakeAs a machine learning engineer or scientist, develop AI-powered solutions to shape the future of the Airbnb agentic growth platform with cutting-edge AI techniques, driving and guiding engineers from inception to production.Thrive at the intersection of technical depth, architectural thinking, and mentorship.Collaborate with cross-functional leaders to build resilient systems that operate globally at scale, and help evolve the foundational building blocks behind AI-powered growth systems.Some example projects you will work onAI-Powered Content Generation: Develop agentic capabilities to autonomously create personalized emails, push notifications, ad copy, and creatives—scaling marketing efforts via more campaigns, greater variant testing, and faster iteration cycles.ML/AI Orchestration for Decisioning: Use AI to determine the optimal audience, message, channel, and timing for communications—shifting marketing decision-making to model-driven intelligence to enhance relevance and minimize message fatigue, improving engagement rates, conversion, and bookings.Proactive Marketing Analyst Agent: Design an AI agent that autonomously identifies new marketing opportunities and converts them into executable campaigns, leveraging world knowledge, proprietary Airbnb intelligence, and deep customer profiles, with a performance-based feedback loop to continuously learn from campaign outcomes and refine future recommendations.A Typical DayWork with large-scale structured and unstructured data; explore, experiment, build, and continuously improve machine learning models and pipelines for Airbnb product, business, and operational use cases.Collaborate with cross-functional partners (product managers, operations, and data scientists) to identify opportunities for business impact; understand, refine, and prioritize machine learning requirements and drive engineering decisions.Hands-on develop, productionize, and operate ML/AI models and pipelines at scale, including both batch and real-time use cases.Leverage third-party and in-house machine learning tools & infrastructure to build reusable, highly differentiating and high-performing machine learning systems; enable fast model development, low-latency serving, and ease of model quality upkeep.Collaborate with engineers to apply ML/AI in their solutions to validate ideas and guide to the right outcomes.Partner with ML/AI engineers in foundations engineering to mentor and develop initiatives that make ML/AI applications a core discipline for non-ML/AI engineers.Your Expertise12+ years of industry experience in applied ML/AI, inclusive of an MS or PhD in relevant fields.Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.Deep understanding of ML/AI best practices (e.g., training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (e.g., neural networks/deep learning, optimization), and domains (e.g., natural language processing, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection).Deep understanding of machine learning best practices (e.g., training/serving skew minimization, A/B test, feature engineering, feature/model selection) and algorithms (e.g., gradient boosted trees, neural networks/deep learning, optimization).Experience with technologies such as Tensorflow, PyTorch, Kubernetes, Airflow (or equivalent), Kafka (or equivalent).Expertise with architectural patterns of large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models).Preferred QualificationsAgentic and Automation: Experience with AI technologies in automating processes and developing agentic solutions and frameworks.Agile Practice for AI Production: Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the applied AI/ML domain.Infrastructure Acumen: Experience building robust testing frameworks for agent behavior validation and continuous improvement, and driving architectural requirements on ML infrastructures.What we offerBase pay range (subject to change): $244,000—$305,000 USD.May be eligible for bonus, equity, benefits, and Employee Travel Credits.
18 days ago