About the Community
Machine Learning and Artificial Intelligence are integral to the Airbnb product. From Trust to Payments, and from Customer Service to Marketing, ML ensures that guests and hosts have the best possible experience. The CS AI product team is dedicated to driving CSxAI (Customer Support x Artificial Intelligence) initiatives by adopting 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, alignment and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning, and guardrails for a wide range of Airbnb applications.
What you will do
As a Principal Machine Learning Engineer, you will be responsible for fine-tuning state-of-the-art LLMs for diverse use cases while optimizing models for high-performance deployment on Airbnb’s ML Infrastructure. You will partner with product managers, software engineers, data scientists, and operation teams to brainstorm, design, and develop AI products such as AI Assistant, Autonomous agents, recommendation systems, travel planning, and many more products that make meaningful impacts in the world of travel.
Your Responsibilities
- Work with large scale structured and unstructured data; explore, experiment, build, and continuously improve foundation models for Airbnb product, business, and operational use cases.
- Create a multi-year tech roadmap that enables our team to stay on the leading edge of the rapidly evolving AI landscape and leverage the best-in-class technologies to deliver customer benefits.
- Continuously evaluate recent and upcoming large foundational models, ensuring the selection and refinement of the highest quality models for enhanced performance and efficiency.
- Hands-on prototype, develop, and productionize LLM models and pipelines at scale, including both batch and real-time use cases.
- Drive key AI architectural decisions for products, and contribute to Airbnb’s ML platform architecture and strategy.
Minimum Qualifications
- PhD in Computer Science, Machine Learning, Mathematics, Statistics, or related technical field.
- 10+ years of experience with developing machine learning models and products at scale from inception to business impact.
- Programming experience in Python and hands-on experience with frameworks such as PyTorch.
- Proven record of training, fine tuning, optimizing models, and inference run-time.
- Post-training experience in areas like data processing for fine-tuning; responsible LLMs; LLM alignment; reinforcement learning; efficient training and inference; language model evaluation; and/or multilingual and multimodal modeling.
- Or specialized experience in runtime optimizations, model quantization, compression, on-device inference, GPU inference, pytorch, kernel development.
Preferred Qualifications
- PhD in AI, machine learning, data science, or related technical fields.
- Publications at peer-reviewed AI conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICCV, and ACL).
- Customer Support Systems: Experience with AI technologies in customer support applications.
- 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 deploying and scaling business-critical AI services and driving architectural requirements on ML infrastructures.