Principal Machine Learning Engineer- LLM Fine-tuning and Optimization

Airbnb
yesterday

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior
Compensation
$ 292K

Job location

Remote

Tech stack

Agile Methodologies
Artificial Intelligence
Computer Programming
Python
Linux kernel
Machine Learning
Product Management
Azure
Unstructured Data
Reinforcement Learning
Data Processing
PyTorch
Large Language Models
Model Validation
Generative AI
AI Platforms
Information Technology
Machine Learning Operations
Virtual Agents

Job description

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.

Requirements

  • 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, * 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

Benefits & conditions

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 Go ad-free with Premium ×, 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

About the company

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., 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.

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