Tech Stack

Description

As a Senior Staff Engineer on the Infrastructure Performance team, you'll optimize performance across Airbnb's fleet and backend stack, working with K8s, observability, data pipelines, and ML infrastructure. You'll partner with cross-functional teams to analyze and deliver performance improvements, evaluate hardware and JVM configurations, and build performance tooling to surface bottlenecks.

Requirements

• 13+ years of relevant performance optimization industry experience in a fast paced, high growth tech environment.
• Working knowledge of processor vectorization activation for various COTS applications.
• Deep software tuning and optimization experience, Java preferred but C++ acceptable.
• Expertise in using metrics to uncover performance issues.
• Familiarity with system hardware as it pertains to performance.
• Familiarity with a public cloud provider (AWS, GCP, Azure) and their IaaS offering (e.g. EC2).
• Familiarity with container and orchestration technologies such as Docker and Kubernetes.
• Excellent communication skills and ability to work well within a team and across engineering teams.
• Strong problem solver and solid performance debugging skills.
• Experience with load testing software either in production or through benchmarking.
• Passionate about efficiency and performance.

Responsibilities

• Work closely with cost and performance cross-functional partners and engineers across all teams at Airbnb to optimize the performance and operating cost of infrastructure.
• Work with largest services to optimize their performance through profiling, analysis and tuning.
• Build distributed performance tooling to collect performance data and automate surfacing performance bottlenecks.
• Lead continuous load testing in production to determine performance bottlenecks and vulnerabilities.
• Work on production performance issues to minimize latency for customers.
• Modernize Airbnb's software stack touching every layer.
• Build infrastructure to deploy latest hardware to AWS Kubernetes clusters.