Senior Staff Machine Learning Engineer, Trust

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: Everyone at Airbnb thinks about trust, but our team obsesses over it daily. At the core of trust is safety, and thus we spend a significant amount of our time and energy keeping the community safe. The Trust team is responsible for developing the technology that helps protect our community and platform from fraud while also ensuring our hosts, guests, homes, and experiences meet our high standards. We constantly work to fight against online fraud (such as monetary loss, compromised accounts, spam and scam in messages, fake inventory, etc.) as well as offline fraud (theft, property damage, personal safety, etc.). We also work on onboarding and screening of users, and think about complex topics like identity and reputation to ensure that every interaction with Airbnb helps build trust in us and our community. Trust Engineering is responsible for the technology vision and development of a complex stack that runs on every key interaction on the platform. Trust Engineering is at the forefront of AI and ML innovation, helping develop novel techniques and advancing the state-of-art in Machine Learning to continually build and maintain trust across our platform. The Difference You Will Make: As a senior technical individual contributor, you will partner closely with our leaders across the broader technical organization helping design, execute and deliver in a complex and collaborative roadmap of Trust engineering efforts that will require collaboration across many parts of the organization and many parts of Airbnb. Although you will be at one of our highest levels of seniority, all individual contributors at Airbnb are Software Engineers which means we expect you to be hands on and contribute code. A Typical day: Define and execute on the long-term ML technical vision and strategy for the Trust organization, identifying key investments, architecting scalable solutions, and championing best practices that advance the state-of-the-art in production ML systems. Serve as a technical leader and mentor to other ML and software engineers across the organization, providing guidance on complex architectural and modeling challenges, and raising the overall technical bar. Drive and deliver large-scale, multi-quarter ML initiatives that span multiple teams, influencing roadmaps and ensuring alignment between platform and product Work with large scale structured and unstructured data, build and continuously improve cutting edge Machine Learning models for Airbnb product, business and operational use cases. 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. Work closely with other trust defense and platform teams to tackle the changing landscape of fraud attacks. Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. Examples include: Anomaly detection models, ML models for continuous risk evaluation, Multimodality and Agentic AI Your Expertise: 12+ years of industry experience in applied Machine Learning 2-3+ years working with LLMs and novel GenAI technologies. Proficiency and proven experience on Agentic AI (frameworks, orchestration, architecture and productionization). A Bachelor’s, Master’s or PhD in CS/ML or related field Strong programming (Scala / Python / Java/ C++ or equivalent) and data engineering 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. genAI, Agentic AI, natural language processing, computer vision, personalization and recommendation, anomaly detection) Experience with  these technologies: AgenticAI, Tensorflow, PyTorch, Kubernetes,  Industry experience building end-to-end Machine Learning and Agentic infrastructure and/or building and productionizing Machine Learning models Exposure to architectural patterns of a large, high-scale software applications (e.g., well-designed APIs, high volume data pipelines, efficient algorithms, models) Experience with test driven development, familiar with A/B testing, incremental delivery and deployment. Experience with the Trust and Risk domain is a plus. Your Location: This 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 with us 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. 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. Equal Employment Opportunity: Airbnb values diversity & belonging and is proud to be an Equal Employment Opportunity employer. All individuals seeking employment at Airbnb are considered without regard to race, color, religion, national origin, age, gender, sex, marital status, ancestry, physical or mental disability, veteran status, gender identity, gender expression, sexual orientation, or any other legally protected characteristic.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.  Pay Range$244,000—$305,000 USD  Reasonable Accommodations: We are committed to providing reasonable accommodations throughout the recruitment process for applicants with disabilities. If you need assistance, or an accommodation, please let your recruiter know once you are contacted about a role. A Note on Recruiting Scams: Scammers sometimes pose as Airbnb recruiters to get money or personal information from candidates. A few things that will always be true for Airbnb’s hiring process: our open roles are posted on Airbnb’s Career’s Page at careers.airbnb.com, and our recruiters correspond only from @airbnb.com or @ext.airbnb.com email addresses. Our recruiters will never ask for your Social Security number, bank account details, passport, or payment app information while you are interviewing.  We’ll also never ask you to pay a fee, send money, deposit or cash a check, or purchase work-related equipment (such as a company laptop) during the interview process. We encourage candidates to remain vigilant of these recruiting scams and not share sensitive information if you do not believe an individual is actually affiliated with Airbnb.