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Staff Machine Learning Engineer, Customer Support Engineering

Worldwide Salaried Open
Job title: Staff Machine Learning Engineer, Customer Support Engineering in USA at Airbnb Company: Airbnb Job description: The Community You Will Join:Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. The Core ML team is the core team responsible for driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting the Generative AI technologies to enable an intelligent, scalable and exceptional service experience. The team develops and enhances various AI models, ML services and tools, including LLM fine-tuning and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.The richness of Airbnb's data, the complexity of its marketplace and the variety innate in our product mean that we need to operate at the state of the art of AI practice. We are committed to investing in long term innovation to solve the complex problems we face, and to do that we need the very best experts in ML and AI to join us.​​The Difference You Will Make:As a machine learning engineer or scientist, your expertise will be pivotal in developing AI-powered products to shape the future of the Airbnb customer experience with cutting-edge AI techniques. You will drive and guide the applied science team to apply agile practice for data science, and partner with product managers, software engineers, and operation teams to brainstorm, design and develop AI products and features from inception to production.A Typical Day:
  • 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.
Your Expertise:
  • PhD in Computer Science, Mathematics, Statistics, or related technical field.
  • 7+ years of industrial experience in building, testing and shipping AI models and products from inception to production; including 1+ years of experience with GenAI.
  • 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 or chatbot related applications.
  • Experience with the entire AI product development lifecycle from incubation to production at scale, following agile practices in the Applied AI/ML domain.
  • Ability to absorb new concepts quickly and integrate them effectively into business processes.
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. 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. Expected salary: Location: USA Apply for the job now! Apply for this job

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