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:

The Identity Defense team plays a critical role in safeguarding Airbnb’s platform by ensuring that every user is who they say they are. We are responsible for preventing identity misuse, detecting fraudulent and duplicate accounts, and enforcing policies against underage use. We operate at the intersection of backend engineering, machine learning, and computer vision to deliver defenses at scale—while minimizing friction for trusted users.

The Difference You Will Make:

Solving Identity Defense Problems Including:

• Identity Misuse Detection - Fraudsters increasingly use fake, stolen, or AI-generated identities to gain access to the platform. Traditional verification signals are no longer enough in the face of sophisticated tampering techniques like deepfakes and synthetic imagery. Our team builds advanced detection systems that combine machine learning, computer vision, and biometric signals to identify and stop bad actors in real time. We continuously evolve our models and systems to keep pace with rapidly advancing AI-driven attack vectors, ensuring Airbnb stays one step ahead.
• Duplicate Account Prevention - Airbnb’s integrity depends on enforcing the principle of one account per person. We’re tackling this using identity linking methods that combine graph-based analysis, embeddings, and device IDs. The scale, complexity, and ambiguity of identity data make this one of the most technically demanding problems at Airbnb.
• Underage User Enforcement - Airbnb prohibits users under the age of 18 from accessing the platform, but verifying age accurately—especially across global markets and varying document types—is a nuanced challenge. Fraudsters exploit OCR weaknesses or use borrowed identities to circumvent our policy. We are investing in government ID parsing improvements, tampering detection, and more robust age inference methods to ensure compliance while minimizing false positives. This space also requires deep collaboration with legal and policy teams to ensure regulatory alignment and defensibility across regions.

A Typical Day:

• Train and deploy machine learning models for identity misuse detection and risk scoring.
• Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases.
• Integrate advanced verification methods, including biometrics and NFC-based flows.
• Collaborate closely with ML, iOS/Android, and web engineers to deliver end-to-end solutions.
• Work collaboratively with cross-functional partners including software engineers, product managers, operations and data scientists, identify opportunities for business impact, understand, refine, and prioritize requirements for machine learning models, drive engineering decisions, and quantify impact.
• Contribute to foundational infrastructure including secure data handling, image processing, model serving, and feature engineering.
• Shape technical direction and influence the team roadmap through long-term strategy and investment planning.
• Mentor other engineers and promote best practices to strengthen Airbnb’s engineering culture and foundations.

Your Expertise:

• 9+ years of industry experience in software engineering, with a focus on applied Machine learning.
• BS/MS/PhD in Computer Science, a related field, or equivalent work experience.
• Strong programming (Scala / Python / Java/ C++ or equivalent) skills.
• Deep understanding of Machine Learning best practices (eg. training/serving skew minimization, A/B test, feature engineering, feature/model selection), algorithms (eg. gradient boosted trees, neural networks/deep learning, optimization) and domains (eg. natural language processing, computer vision, personalization and recommendation, anomaly detection).
• Industry experience building end-to-end Machine Learning infrastructure and/or building and productionizing Machine Learning models.
• Strong collaboration skills and experience working with cross-functional teams.
• Comfortable navigating ambiguity and driving projects from concept to production.
• Experience with test driven development, familiar with A/B testing, incremental delivery and deployment.
• Experience with computer vision systems (e.g., face detection, liveness, tampering detection) is a plus.
• Experience with the Trust and Risk domain is a plus.

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.