
Staff Machine Learning Engineer, AI Enablement
Job role insights
Date posted
May 29, 2025
Closing date
June 23, 2025
Hiring location
USA
Experience
9+ Years
Description
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:
As a Staff Software Engineer on the AI Enablement team, you will play a critical role in accelerating the development and deployment of AI-powered applications at Airbnb. You’ll work directly with product teams across the company to improve iteration speed, application quality, and operational scale. Your insights and technical expertise will also shape the future of our machine learning infrastructure, enabling hundreds of ML engineers and data scientists to build world-class AI experiences. Come build the future of AI at Airbnb.The Difference You Will Make:
In this role, you’ll accelerate the development and deployment of AI-powered applications at Airbnb. You will work closely with teams shipping GenAI-powered use-cases to improve their iteration speed, application quality, and scale. Your experience and feedback will help shape the shared machine learning infrastructure used across the company.A Typical Day:
- Collaborate closely with teams across Airbnb—such as Customer Support, Search Relevance, and Trust & Safety—to deliver impactful AI-driven product features.
- Develop flexible, high-leverage tooling and infrastructure to support the use of foundational models (language and vision) across Airbnb.
- Build flexible GenAI Tooling to accelerate the efforts of Airbnb teams using foundational language / vision models to power next-gen product experiences
- Work with cutting-edge open-source technologies including LangGraph, Hugging Face, PyTorch, Ray etc.
- Use OSS technologies such as LangGraph, Hugging Face, PyTorch, Ray, Kubernetes, JupyterHub, etc.
- Rapidly prototype, evaluate, and iterate on GenAI applications that unlock new product capabilities.
- Champion clean abstractions and reusable components that balance speed, scalability, and reliability.
Your Expertise:
- 9+ years of industry experience in applied Machine Learning, inclusive MS or PhD in relevant fields.
- Strong programming (Scala / Python / Java / C++ or equivalent) and data engineering skills.
- Deep familiarity with machine learning engineering practices, particularly around training and deploying PyTorch, TensorFlow, or Hugging Face models in production. Prior experience with deploying or supporting production ML systems at scale.
- Passionate about AI with a strong grasp of current trends in Generative AI, LLMs, and related technologies.
- Fast learner with a bias for execution—able to ramp up quickly on new tools and technologies.
- Excellent collaboration and communication skills—able to earn the trust of cross-functional partners and influence without authority.
- You may currently hold titles such as ML Engineer, Applied Scientist, ML Infrastructure Engineer, or Data Scientist, but what sets you apart is your hunger to learn, ship, and support AI systems in production. You’re not just excited about what’s next in AI—you’re ready to build it.
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.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
$204,000—$255,000 USD