• Lead a team of ML/Ops engineers in deploying and managing Machine Learning models. • Build and enhance capabilities to seamlessly integrate ML models into existing pipelines. • Collaborate with cross-functional teams to understand project requirements and ensure successful deployment. • Provide ongoing support to accommodate surges in requirements, focusing on scalability and efficiency. • Utilize Python for scripting and automation tasks. • Work with Cloud platforms, particularly Azure and GCP to optimize machine learning workflows.

• 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

• In this Senior Staff role, you will set technical direction and lead execution for ML evaluation and the end-to-end data flywheel powering CSxAI products (e.g., assistive agents, issue resolution, and tooling). • Your work will define how we measure quality, how we turn feedback into learning signals, and how we continuously improve models and products safely and efficiently. • You will partner closely with product, engineering, design, operations to build evaluation systems that are trusted, scalable, and actionable - connecting offline metrics to online outcomes. • Work 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. • Work collaboratively with cross-functional partners including product managers, operations and data scientists, to identify opportunities for business impact; understand, refine, and prioritize requirements for machine learning, and drive engineering decisions. • Hands-on develop, productionize, and operate Machine Learning models and pipelines at scale, including both batch and real-time use cases. • Leverage third-party and in-house Machine Learning tools & infrastructure to develop reusable, highly differentiating and high-performing Machine Learning systems, enable fast model development, low-latency serving and ease of model quality upkeep.

• Working with our distributed training stack to start training runs and tracking them closely. • Contributing to our ML codebases and adding new models, algorithms and features. • Experimenting with new model architectures and designs, and getting them production ready. • Training and finetuning models, and adapting them to our products by taking tester feedback and iterating over the trained models.