Amazon.com Services LLC

Technology

AppliedScientistII,GenAIEvaluationMedia(GEM)

$143–193k Seattle, Washington, United States FULL TIME
Market Sentiment
HIGH DEMAND

Neural analysis suggests this role is
optimal for Mid candidates.

The Brief

“Applied Scientist II, GenAI Evaluation Media (GEM) at Amazon.com Services LLC. Skills: Computer Vision, Generative AI, Machine Learning. Develop science primitives. Design visual agentic systems”

Industry & Context.

Technology
Problems you'll solve

Rigorous research skills; Practical engineering instincts; Tackle complex technical problems

What They're Looking For.

Must Have

Master's degree and 4+ years experience, PhD or Master's degree, 4+ years CS, CE, ML experience, Building models for business application, Programming in Java, C++, Python

Nice to Have

Investigating, designing, prototyping, delivering solutions, CS, CE, ML research experience, Building machine learning models, Developing algorithms for business application, Developing deep learning algorithms, Computer vision algorithms experience, Generative AI tools usage, Learn effective prompting, Learn evaluation practices, Recognize generative AI opportunities

What You'll Do.

Develop science primitives

Design visual agentic systems

Define metrics and success criteria

Validate asset effectiveness

Own end-to-end delivery

Production deployment

Stay current with AI/ML advances

Identify application opportunities

Drive development of agentic systems

Deploy agentic systems

Maintain scientific standards

Maintain engineering standards

Tackle complex technical problems

Focus on customer value

Contribute to scientific excellence

Present at science forums

Publish at science forums

Partner with product teams

Partner with engineering teams

Deliver customer-facing features

Collaborate with scientists

Collaborate with engineers

Align on technical approaches

Communicate research findings

Communicate technical trade-offs

How You'll Work.

Team & Collaboration

Cross-functional partners; Scientists across Amazon; Engineers across Amazon; Product teams; Engineering teams

Communication Scope

Communicate findings; Communicate trade-offs

Full Job Description

The North America Stores GenAI Evaluation Media (GEM) team is seeking an Applied Scientist to help shape the future of visual shopping experiences. We're building CXs and foundational capabilities to understand, enhance, and generate real-time GenAI imagery, videos and CXs that inspire customers and drive purchase confidence, towards our vision to be the leader in visual media. Specifically, the charter will focus on visual agentic experiences, multi-modal personalization, and real-time image/video generation, looking ahead as customer shopping continues to inspirational assistant-driven experiences. As an Applied Scientist on the team, you will drive the research and development of agentic AI capabilities that inform and guide the customer's shopping journey through visuals. This includes building core science primitives for multimodal understanding, visual content generation and editing, personalized virtual try-on, and automated quality assurance. You will develop the foundational capabilities that enable customers to express and discover styles through multimodal conversation and receive personalized, visual responses that bring their ideas to life. Your scientific approach will emphasize accurate, real-time visual understanding and generation, contextual understanding, and scalable personalization, enabling agentic AI to actively collaborate with customers to achieve their style goals. You will bring together computer vision, natural language processing, generative AI, and human-centered design to create agentic shopping experiences that are as intuitive as talking to a human specialist with a deep domain knowledge base. Success requires establishing robust metrics, collaborating with cross-functional partners, validating asset effectiveness across diverse customer touch points, and staying at the forefront of rapid advances in AI technology. The ideal candidate will have deep technical expertise in Computer Vision, Generative AI, or related fields with a stron

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