Principal Machine Learning Engineer

Role Overview

Machine Learning and Artificial Intelligence are at the heart of the Airbnb product, impacting everything from Trust to Payments, Customer Service, and Marketing. The CS AI product team drives 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 guardrail for a wide range of applications at Airbnb.

The Difference You Will Make

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 agent, recommendation, travel planning, and many more products that make meaningful impacts in the world of travel.

A Typical Day

• 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.

Your Expertise

• 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.