Senior Applied Scientist: GenAI for Brand Stores

Amazon; Seattle (WA); On-site; USD 167,000 - 226,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon is seeking a Senior Applied Scientist for the Brand Stores initiative within Amazon Ads. You will own the science strategy and hands-on development of AI-powered brand experiences at Amazon scale, combining frontier research with production systems and a strong business sense.

You will lead the gap between research and real-world impact, shaping what we build and where we invest next across GenAI-enabled storefronts and advertising experiences.

Qualifications

• 3+ years of building machine learning models for business applications.
• PhD, or Master's degree and 6+ years of applied research experience.
• Experience programming in Java, C++, Python or related language.
• Experience in development in the last 3 years, or experience in developing and deploying LLMs in production on GPUs, Neuron, TPU or other AI acceleration hardware.
• 3+ years in digital advertising technology.

Responsibilities

• Build intelligent systems for Brand Stores leveraging generative AI to improve advertiser and shopper experiences.
• Define a multi-year science vision and roadmap.
• Architect ahead of the GenAI curve and position scalable solutions.
• Design and run rigorous A/B experiments with deep data analysis.
• Communicate complex technical ideas to diverse audiences.

Skills

Machine learning models

Applied research

Programming in Java

Programming in C++

Programming in Python

Digital advertising

Education

PhD or Master's with 6+ years of applied research

Tools

Java

C++

Python

Job description

Amazon is seeking a Senior Applied Scientist for the Brand Stores initiative within Amazon Ads. You will own the science strategy and hands-on development of AI-powered brand experiences at Amazon scale, combining frontier research with production systems and a strong business sense.

You will lead the gap between research and real-world impact, shaping what we build and where we invest next across GenAI-enabled storefronts and advertising experiences.