Staff Machine Learning Engineer, AI Experience

Remote Full-time
Job title: Staff Machine Learning Engineer, AI Experience in USA at Airbnb

Company: Airbnb

Job description: The Community You Will JoinJoin Airbnb's new AI Experience Team-a collaborative group of engineers, designers, and product managers focused on creating modern, AI-powered interfaces that transform how our guests and hosts engage with Airbnb. We're building the “ultimate concierge”, a next-generation platform that leverages generative AI and agentic systems to deliver deeply personalized and adaptive user experiences.The Difference You Will MakeAs a Staff Machine Learning Engineer, you bring specialized depth and breadth of expertise to lead complex AI initiatives. You will architect solutions that push the boundaries of what's possible, drive innovation across diverse teams, and guide key projects from conception to production. Your work will shape Airbnb's AI-forward future. From prototyping agentic multi-step workflows to integrating Retrieval-Augmented Generation (RAG), you will be developing cutting-edge systems that move beyond 2000s-era user interfaces toward intuitive, real-time AI experiences. Your contributions will be integral to transforming the Airbnb app into an ever-evolving platform that knows you, adapts to your needs, and drives our broader mission of creating a world where anyone can belong anywhere.A Typical Day

Architect and develop large-scale AI solutions, from data pipelines and fine-tuning methodologies to multi-step agentic workflows, transforming Airbnb's platform into a deeply personalized and intelligent concierge.
Collaborate with cross-functional partners to develop prototypes that push the boundaries of generative AI, then transition them into high-impact production features.
Develop prototypes that embed state-of-the-art generative AI capabilities, ensuring they meet production-level metrics for reliability, scalability, and ethical alignment.
Drive data quality, leveraging advanced synthetic data generation techniques and robust analytics to continuously improve AI performance.
Serve as a technical mentor, conducting knowledge-sharing sessions and code reviews that uplift team-wide expertise in AI and machine learning.
Present progress, insights, and strategic recommendations to senior leadership, influencing the broader AI roadmap at Airbnb.
Your Expertise

5+ years of professional machine learning engineering experience, including proven leadership on AI/ML projects at scale, ideally at the Staff Engineer level or above.
Hands-on experience building and shipping generative AI solutions, emphasizing Retrieval-Augmented Generation (RAG), agentic workflows, and large language models.
Demonstrated success improving AI data quality through synthetic data techniques, adversarial testing, or advanced data annotation pipelines.
Strong proficiency in backend engineering and cloud-based architectures that support high-volume, real-time AI workloads.
Excellent communication skills and a track record of cross-functional collaboration, translating complex technical concepts into actionable insights for varied audiences.
Passion for responsible and ethical AI, designing solutions with guardrails that prioritize accuracy, user trust, and inclusiveness.
Come shape the future of travel with us. As a Staff Machine Learning Engineer on the AI Experience Team, your work will directly impact millions of guests and hosts worldwide, transforming how people explore, connect, and belong anywhere.Your LocationThis 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 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.

Expected salary:

Location: USA

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