Nouveau Amazon

Software Development Engineer – Search Performance

  • San Francisco (City and County of San Francisco)
  • Conception / Génie civil / Génie industriel

Description de l'offre


The Amazon Search team creates powerful, customer-focused search solutions and technologies. Whenever a customer visits an Amazon site worldwide and types in a query or browses through product categories, Amazon Search goes to work. We design, develop, and deploy high performance, fault-tolerant distributed search systems used by millions of Amazon customers every day.

As a Software Development Engineer on this team you will:

· Design and implement the infrastructure for regularly quantifying and characterizing performance and scalability of Amazon Search service and its subsystems in an automated manner.
· Design and implement persistence and visualization systems for tracking performance metrics and trends over an extended period of time.
· Create tools to enable development teams to test the performance impact of their changes in a self-service manner.
· Identify opportunities for reducing customer facing latency or CPU/memory/network resource consumption, and work with development teams to realize them.
· Evaluate hardware choices for various Search workloads and influence availability of appropriate alternatives from AWS.

Joining this team, you will experience the benefits of working in a dynamic, entrepreneurial environment, while leveraging the resources of (AMZN), one of the world's leading internet companies. We provide a highly customer-centric, team-oriented environment in our offices located in Palo Alto, California.

Profil recherché


· Bachelor's Degree in Computer Science, Engineer, Math, or related fields.
· At least 5 years programming in Python, C++, or Java, and proficiency in shell scripting.
· At least 2 years of experience with in-depth analysis of performance issues related to large scale systems software infrastructure. Identifying bottlenecks and opportunities for improvements.
· At least 2 years of experience with large-scale distributed systems.