Senior Staff Machine Learning Engineer

Summary

Join Airbnb's Community Support Engineering team as a Senior Staff Machine Learning Engineer and help shape the future of customer experience. You will leverage cutting-edge AI techniques to develop AI-powered solutions, collaborating with cross-functional leaders to build scalable, global systems. Your responsibilities will include building a unified case management system, designing AI workflow orchestration, modernizing the Delivery Management Console, establishing shared data foundations, and delivering next-generation matching capabilities. A typical day involves working with large-scale data, collaborating with cross-functional partners, developing and operating ML models, and mentoring other engineers. This role requires a PhD in a related technical field, 10+ years of experience in building AI models and products, and deep knowledge of machine learning best practices. The position is US-remote eligible with occasional office work.

Requirements

• Educational Background : PhD in Computer Science, Mathematics, Statistics, or related technical field
• Industry Experience : 10+ years of experience in building, testing and shipping AI models and products from inception to production; including 2+ years of experience with GenAI
• Leadership Experience : 10+ years experience leading and guiding machine learning and AI projects that deliver sizable impact as a senior IC
• Technical Proficiency : Deep knowledge and hands-on experience with Machine Learning best practices (eg. training/serving skew minimization, feature engineering, feature/model selection), algorithms (eg. neural networks/deep learning, optimization) and domains (eg. NLP, computer vision, personalization, search and recommendation, marketplace optimization, anomaly detection)

Responsibilities

• Building a unified, platform-native case management system (AirCase), abstracted via Viaduct APIs and replacing legacy CRM systems
• Designing scalable AI workflow orchestration to power agent co-pilot tools and intelligent response automation
• Modernizing our Delivery Management Console (DMC) to include AI powered real-time performance insights, outlier detection, and agent coaching tools
• Establishing shared data foundations to enable AI/ML solutions, feedback loops, and personalization across the support journey
• Delivering next generating matching capabilities ( Routing) so incoming customer contacts are matched to the best agents using AI and Intelligence to deliver personalized and differentiated support experiences
• 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
• Collaborate actively with engineers to apply ML / AI in their solutions to help validate ideas and guide to the right outcomes
• Partner with other ML Engineers in foundations engineering to mentor and develop initiative to make ML application a core discipline for non ML engineers

Preferred Qualifications

• Agentic 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

Benefits

• Bonus
• Equity
• Benefits
• Employee Travel Credits