Senior Staff Machine Learning Engineer, Community Support Engineering

Airbnb is a global platform that connects hosts and guests, and they are seeking a Senior Staff Machine Learning Engineer to drive AI-powered product development. This role involves collaborating with cross-functional teams to enhance machine learning models and pipelines that improve customer experiences at Airbnb.

Responsibilities:

• 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

Requirements:

• PhD in Computer Science, Mathematics, Statistics, or related technical field
• 10+ years of experience in building, testing and shipping AI models and products from inception to production; including 2+ years of experience with GenAI
• 5+ years experience leading and guiding applied science/ machine learning teams that deliver large impact as a senior IC
• Deep knowledge and hands-on experience with Machine Learning best practices (eg. training/serving skew minimization, A/B test, 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)
• Experience with AI technologies in customer support applications
• Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain
• Experience building robust testing frameworks for agent behavior validation and continuous improvement, and driving architectural requirements on ML infrastructures
• Ability to absorb new concepts quickly and integrate them effectively into business processes