Senior Applied Science Manager — AI-Driven Search

Amazon Inc.; Irvine (CA); On-site; USD 219,000 - 296,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC in Irvine, CA is seeking a Senior Applied Science Manager to lead the development of AI/ML solutions for adaptive search experiences serving hundreds of millions of customers.

You will guide cross-functional teams of scientists, engineers, and product managers to integrate LLMs into existing search systems while maintaining low latency and high-quality results. The role emphasizes strategy, experimentation, and impact across large-scale data and real-time decisions.

Qualifications

• 10+ years of experience building large-scale ML/AI solutions at Internet scale.
• Master's degree in Computer Science with ML/AI/Statistics focus.
• Experience building large-scale ML/AI solutions at Internet scale.
• Experience distilling informal customer requirements into problem definitions amid ambiguity and competing objectives.
• Experience hiring and leading scientists and mentoring junior members to career growth.

Responsibilities

• Develop a comprehensive science strategy for adaptive search experiences and LLM integration.
• Lead cross-functional teams through experiments to drive measurable business impact.
• Balance latency requirements with real-time personalization and system performance.

Skills

Large-scale ML/AI systems

Team leadership

Problem formulation under ambiguity

Hiring and mentoring

Education

M.S. in Computer Science (ML/AI/Stats)

PhD in Computer Science (ML/AI/Stats)

Tools

AWS

Hadoop

Spark

Pig

Hive

Java

C++

Python

R/MATLAB

Job description

Amazon.com Services LLC in Irvine, CA is seeking a Senior Applied Science Manager to lead the development of AI/ML solutions for adaptive search experiences serving hundreds of millions of customers.

You will guide cross-functional teams of scientists, engineers, and product managers to integrate LLMs into existing search systems while maintaining low latency and high-quality results. The role emphasizes strategy, experimentation, and impact across large-scale data and real-time decisions.