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:
At Airbnb, our mission is to create a world where anyone can belong anywhere. The AI Compute team is responsible for delivering and operating the GPU platform and infrastructure that powers AI at Airbnb.
Airbnb is a member of the Cloud Native Compute Foundation’s end user community and regularly meets with peer companies to discuss cloud native engineering challenges at scale.
The Difference You Will Make:
As a Senior Software Engineer on the AI Compute team, your role is to serve as the technical leader, overseeing the entire lifecycle of Airbnb’s Kubernetes-based GPU platform. You will be instrumental in boosting the efficiency and effectiveness of the Cloud Infrastructure organization by significantly enhancing all facets of the Machine Learning (ML) engineering experience. This platform is the critical foundation that supports all AI Compute features related to security, networking, developer experience, and operational efficiency.
Your team will provide the reliability, scalability, security, and developer experience necessary for ML teams to deliver first class experiences to Airbnb Guests and Hosts around the world.
A Typical Day:
- Provide technical leadership on high-impact projects
- Influence and coach a distributed team of engineers
- Drive reliability, cost efficiency and capability enhancements for GPU fleet
- Facilitate cross-team alignment on goals, outcomes, and timelines
- Manage project priorities, deadlines, and deliverables
- Contribute to and execute the multi-year strategy for Airbnb’s AI Compute Platform
- Design, develop, test, deploy, maintain, and enhance the Airbnb AI Compute Platform
Your Expertise:
- BS, MS or Ph.D. in computer science or related field, or equivalent work experience
- 5+ years of relevant work experience in infrastructure
- 2+ years of expertise with a public cloud provider (AWS, GCP, Azure) and their infrastructure as a service offering (e.g. EC2).
- Experience setting technical direction, planning, and successfully executing on large projects spanning multiple teams
- Kubernetes Experience is required.
- ML Infrastructure (LLM fundamentals, tuning, optimization) Experience is preferred.
- Passionate about efficiency, availability, quality and developer experience.
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. Click here for the up-to-date list of excluded states. This list is continuously evolving, so please check back with us if the state you live in is on the exclusion list. If your position is employed by another Airbnb entity, your recruiter will inform you what states you are eligible to work from.
Our Commitment To Inclusion & Belonging:
Airbnb is committed to working with the broadest talent pool possible. We believe diverse ideas foster innovation and engagement, and allow us to attract creatively-led people, and to develop the best products, services and solutions. All qualified individuals are encouraged to apply.
We strive to also provide a disability inclusive application and interview process. If you are a candidate with a disability and require reasonable accommodation in order to submit an application, please contact us at: [email protected]. Please include your full name, the role you’re applying for and the accommodation necessary to assist you with the recruiting process.
We ask that you only reach out to us if you are a candidate whose disability prevents you from being able to complete our online application.
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.
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