Amazon Advertising is one of Amazon's fastest growing and most profitable businesses. Amazon's advertising portfolio helps merchants, retail vendors, and brand owners succeed via native advertising, which grows incremental sales of their products sold through Amazon. The primary goals are to help shoppers discover new products they love, be the most efficient way for advertisers to meet their business objectives, and build a sustainable business that continuously innovates on behalf of customers. Our products and solutions are strategically important to enable our Retail and Marketplace businesses to drive long-term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day.
The Creative X org within Amazon Advertising builds the science that decides what is in an ad creative and whether that creative is good, safe, and on-brand. As advertisers and our own generative tools produce creative assets at massive scale, the hard problem shifts from making content to understanding it: scoring quality and aesthetics, catching policy and safety violations before they reach a customer, extracting structured meaning from images and video, and measuring whether a creative meets the bar. We work across computer vision, vision-language models, multimodal understanding, content moderation and trust and safety, and evaluation science. The models this team builds run in production as the quality and safety layer across the entire creative lifecycle, from the moment an asset is generated or uploaded through to what advertisers and shoppers ultimately see.
We are seeking a science leader to own Creative Understanding end to end. This is a hands-on leadership role: you will directly lead a team of applied scientists while managing and growing team leads and managers as the charter expands across quality assessment, safety and moderation, evaluation and benchmarking, metadata and attribute extraction, brand and logo detection, and content similarity and retrieval. The right leader sets the scientific direction for how we measure and safeguard creative quality at scale, holds the tension between long-term evaluation research and near-term production delivery, and is accountable for the models this team ships. You will be an inventor at heart who is equally comfortable going deep on a vision-language architecture with a scientist and building the team mechanisms, hiring bar, and roadmap that let a growing organization execute.
Key job responsibilities
This role leads the applied science team responsible for creative quality, safety and moderation, and content understanding across images, video, and multimodal assets. Responsibilities include:
* Own the scientific direction for creative quality assessment, content moderation and trust and safety, evaluation and benchmarking, and multimodal content understanding.
* Directly lead a team of applied scientists while managing and developing subordinate leads and managers as the portfolio grows across understanding sub-domains.
* Drive end-to-end applied science programs with high ambiguity, scale, and complexity, and be accountable for the resulting models in production.
* Advance the science of evaluation: define how we measure creative quality, safety, and brand compliance, and build the benchmarks and metrics the broader org relies on.
* Research and apply new approaches in computer vision, vision-language models, and multimodal understanding, including quality and aesthetics scoring, safety classification, attribute and metadata extraction, and brand and logo detection.
* Recruit, mentor, and grow high-performing applied scientists and science managers, and raise the hiring and technical bar for the team.
* Establish team mechanisms for planning, document and design reviews, and cross-functional partnership with product and engineering.
