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Staff Software Engineer, Performance

Airbnb
1 month ago
Full-time
Remote
Worldwide
Remote Engineering

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:

The Infrastructure Performance team's charter is to optimize performance across the fleet and throughout the backend stack. The scope of infrastructure systems the Performance Team work on includes: K8s services, Observability infra, Data pipelines, ML infrastructure etc. each requiring different skills.

The Difference You Will Make:

In areas of strategic importance, the team engages deeply and effectively with their cross-functional partners to analyze, scope and deliver performance improvement. They achieve this by building and maintaining strong cross-team relationships grounded in sound technical judgement and deep technical engagement. The team is also responsible for the evaluation of the latest hardware offerings from across the industry to get the most optimal performance and minimize the footprint of the fleet. The team is also responsible for evaluating the performance of the latest JVM with respect to hardware configurations and OS features. Finally the team also owns key pieces of Performance Infrastructure in performance observability in resources(cpu, memory, locks, etc) in our services and make this data available to all backend teams across the tech organization. You will closely work with a group of accomplished engineers and report to the Senior Engineering Manager, Infrastructure.

A Typical Day:Β 

  • Work closely with cost and performance cross-functional partners and engineers across all teams at Airbnb to optimize the performance and the operating cost of our infrastructure.
  • Work with our largest services to optimize their performance through profiling, analysis and tuning.
  • Build distributed performance tooling to constantly collect performance data and develop automation to surface performance bottlenecks.
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