Senior Software Engineer, Offline Risk
Airbnb, Seattle, WA or San Francisco, CA
Who wouldn't want to work here?
What is Trust at Airbnb?
Over two million people stay on Airbnb every night and the Trust Engineering team keeps our hosts and guests safe and supported throughout the entire Airbnb experience.
As part of the Trust Engineering team you will be in charge of designing and building scalable and robust systems to detect and mitigate fraud across our entire platform. You will be deeply involved in the technical details of building highly available and real-time risk detection services in close collaboration with product, data science and operations teams to understand ever evolving attack vectors and to make Airbnb the most safe and trusted community.
There are still many unsolved problems to tackle in both online and offline risk, and we're looking for talented engineers to solve these challenges with us.
What is a Backend Engineer on Trust at Airbnb?
The Offline Risk team is dedicated to creating the safest travel platform. We spend our effort on keeping the Airbnb community safe from risks in the physical world and upholding the community expectation around safety. Recently, we launched several initiatives including manual review of reservation, underaged user restriction, security deposit, real-time risk detection model at booking time, and NLP model for user reviews. The team operates in diverse tech stacks and across organizations and functions.
As an engineer on the Offline Risk team, you help keep Airbnb users safe by working across diverse teams and systems to enable sophisticated safety strategies. You are eager to understand complex systems top to bottom and thrive working across technologies and codebases. Your contributions take a variety of shapes:
- Architecting powerful end-to-end user products to keep Airbnb community safe
- Building novel machine learning models to detect risk or help humans make decisions
- Developing scalable, real-time risk detection into Airbnb services
- Working with cross-functional teams with design, product, data science, and research partners to drive engineering decisions
- Improve and extend the fraud investigation tools used by Airbnb operations. These tools aggregate and display data from across Airbnb’s internal systems, and enable our operations team to make accurate, efficient decisions on potentially fraudulent transactions, fake accounts, and more.
- Develop machine learning models to detect risk that informs product decisions
- Create products to deter bad actors off of Airbnb and to restrict their usage
- Provide and educate guest and host safety standards and mitigate vulnerabilities
- 5+ years industry experience
- Experience with Java / Scala is preferred
- Passion for delivering products end-to-end, from ideation through planning and scoping to implementation and experimental A/B testing
- Exposure to architectural patterns of large, high-scale web applications, such as well-designed APIs, high volume data pipelines, and efficient algorithms.
- Experience or desire to work on machine learning algorithms and end-to-end model development
- Experience or desire to work collaboratively in cross-functional teams with design, product, data science, operations, and research partners.
- Competitive salaries
- Quarterly employee travel coupon
- Paid time off
- Medical, dental, & vision insurance
- Life insurance and disability benefits
- Fitness discounts
- Flexible Spending Accounts
- Apple equipment
- Commuter subsidies
- Community involvement (4 hours per month to give back to the community)
- Company sponsored tech talks and happy hours
- Breakfast, lunch, and dinner
- Much more...
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Founded in August of 2008 and based in San Francisco, California, Airbnb is a trusted community marketplace for people to list, discover, and book unique accommodations around the world — online or from a mobile phone. Whether an apartment for a night, a castle for a week, or a villa for a month, Airbnb connects people to unique travel experiences, at any price point, in more than 33,000 cities and 192 countries.
Want to learn more about Airbnb? Visit Airbnb's website.
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