Airbnb, a global hospitality platform founded in 2007, is seeking a Staff Software Engineer to join their Trust team. This role is crucial in maintaining the safety and security of Airbnb's community of over 5 million hosts and billions of guest arrivals worldwide.
The position sits within the Fraud Prevention & Safety team, which is dedicated to detecting and mitigating both online and offline fraud while ensuring high standards for hosts, guests, homes, and experiences. The team tackles challenges ranging from monetary loss and compromised accounts to property damage and personal safety concerns.
As a Staff Software Engineer, you'll be at the forefront of building highly available, real-time risk detection services. You'll work closely with product managers, data scientists, and operations teams to understand evolving attack vectors and strengthen Airbnb's trust and safety infrastructure. The role requires hands-on coding and technical leadership, with responsibilities including designing scalable distributed systems, developing machine learning models, and mentoring other engineers.
The position offers a competitive compensation package ranging from $204,000 to $255,000 USD, plus potential bonuses, equity, and Employee Travel Credits. This is a remote-eligible position within the United States, with occasional office visits or offsites as needed.
The ideal candidate brings 9+ years of industry experience, strong programming skills in languages like Scala, Python, or Java, and expertise in large-scale software applications. Experience with trust and risk domains and machine learning is highly valued. This role presents an exceptional opportunity to impact millions of users while working with cutting-edge technology in fraud prevention and community safety.
Airbnb is committed to inclusion and belonging, welcoming diverse perspectives and providing reasonable accommodations for candidates with disabilities. Join a team that's shaping the future of trust in the sharing economy while working with some of the industry's most challenging and rewarding technical problems.