Software Development Manager, Core Search

The Search Engine organization designs, builds, and operates highly performant, fault-tolerant and scalable distributed search engine used by millions of Amazon customers worldwide every day.We are evolving our search engine to better understand natural language queries and to be more personalized. This involves leveraging LLMs and other Deep Learning models in different parts of the search stack to improve the search experience.Ideal candidates are expected to have an extensive background in distributed systems and experience with machine learning infrastructure. Strong candidates will have knowledge of LLM fundamentals and some experience in GPU programming.Key job responsibilitiesTechnical LeadershipLead development of LLM/deep-learning relevance and ranking systems serving billions of queries at scaleImprove search engine efficiency to reduce infrastructure costDrive architecture and design decisions aligned with the search org visionOwn full development and operations lifecycle of your team’s productsTeam & People ManagementManage engineering team: staffing, day-to-day execution, delivery commitments, and mentoring and career growthReport on development progress, quality, operations, and system performanceStrategy & CollaborationDefine long-term vision and growth plans in partnership with Science and Engineering leadersSet development priorities and evangelize the team”s work across the org

Ideal candidates are expected to have an extensive background in distributed systems and experience with machine learning infrastructure. Strong candidates will have knowledge of LLM fundamentals and some experience in GPU programming.

The Search Engine organization designs, builds, and operates highly performant, fault-tolerant and scalable distributed search engine used by millions of Amazon customers worldwide every day.

We are evolving our search engine to better understand natural language queries and to be more personalized. This involves leveraging LLMs and other Deep Learning models in different parts of the search stack to improve the search experience.