Staff Software Engineer, Communication Products
Airbnb · Remote (United States) · Software Engineering
About this role
Airbnb is hiring a staff-level Software Engineer as a remote position. The posting calls out experience with LLMs, NLP, Feature Engineering, Prompt Engineering and roughly 9+ years of relevant work. Listed education preference: a bachelor's degree or equivalent. Compensation is listed at $204,000–$255,000 per year.
- Role
- Software Engineer
- Function
- software engineering
- Level
- staff
- Track
- Tech leadership
- Employment
- Full-time
- Location
- Remote (United States)
- Work mode
- Remote
- Experience
- 9+ years
- Education
- Bachelor's degree
- Department
- Software Engineering
More roles at Airbnb
Job description
from Airbnb careersAirbnb 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:
Messaging is a critical component in building connections with our users. Our mission as the Communication Products team is to build a first-class messaging experience at Airbnb, bringing together guests and hosts across the world. We are investing heavily in machine learning to make these conversations smarter, safer, and more productive. As a staff software engineer on this team, you'll lead the technical vision for ML-powered messaging features: architecting and delivering intelligent capabilities end-to-end, partnering deeply with ML and product teams, and raising the engineering bar across the organization.
The Difference You Will Make:
As a Staff Engineer on the team, you will define and drive the technical strategy for integrating ML capabilities into Airbnb's messaging products, including smart replies, message classification, content moderation, translation, and conversational assistance. You will also own the full lifecycle of ML-powered features: from prototyping and experimentation through launch, monitoring, and iteration. In addition, you will help drive key technical deliverables for the larger Communications organization.