Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences that make it possible for guests to connect with communities in a more authentic way.

The Community You Will Join:

Machine Learning and Artificial Intelligence are at the heart of the Airbnb product. From Trust to Payments, and from Customer Service to Marketing we rely on ML to ensure that guests and hosts have the best possible experience with Airbnb.

The CS AI product team is 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, alignment and optimization, RAG/Search, LLM evaluation and testing automation, feedback-based learning and guardrail for a wide range of applications in Airbnb.

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 agent, recommendation, 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

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. Click here 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.

Our Commitment To Inclusion & Belonging:

Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.

We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: reasonableaccommodations@airbnb.com. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.

We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.

How We'll Take Care of You:

Our job titles may span more than one career level. The actual base pay is dependent upon many factors, such as: training, transferable skills, work experience, business needs and market demands. The base pay range is subject to change and may be modified in the future. This role may also be eligible for bonus, equity, benefits, and Employee Travel Credits.

Pay Range

$292,000—$365,000 USD

Principal Machine Learning Engineer- LLM Fine-tuning and Optimization