The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you\'re energized by solving complex challenges and pushing the boundaries of what\'s possible with AI, join us in shaping the future of advertising.
As for Brand Stores (e.g., amazon.com/lego and 1MM+ more), we are the exclusive destination for brand owners to showcase their content and product catalog through custom creative, seamlessly integrated with Amazon Stores and ads products, attracting millions of daily visits.
We\'re reinventing how brands and shoppers connect. Using generative AI, we\'re building the next generation of brand-centric storefronts, reimagining store creation, optimization, performance analysis, and customer insights through state-of-the-art GenAI technologies.
As a Senior Applied Scientist on the team, you\'ll own the science strategy and hands-on development of AI-powered brand experiences at Amazon scale. You\'ll operate at the intersection of frontier research and high-impact production systems, with the autonomy to shape what we build, how we build it, and where we invest next. This role combines science leadership, technical depth, product intuition, and business acumen.
#GenAI
Key job responsibilities
If you\'re energized by solving complex challenges and pushing the boundaries of what\'s possible with AI, this is the role.
* Build intelligent systems for Brand Stores. Develop AI-powered solutions leveraging generative models to optimize both advertiser and shopper experiences, measurably improving Brand Store performance.
* Define a multi-year science vision and roadmap. Translate customer needs into actionable plans for applied scientists and engineering teams, blending science leadership, technical depth, product intuition, and business acumen.
* Architect ahead of the GenAI curve. Anticipate where generative AI is heading over a multi-year horizon and position solutions to capitalize on compounding advances.
* Experiment rigorously. Design and run A/B experiments grounded in deep data analysis to validate hypotheses and quantify impact.
* Communicate with clarity. Translate complex technical ideas into compelling narratives for both technical and non-technical audiences.
About the team
The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through industry leading generative AI technologies, revolutionizing how millions of customers discover products and engage with brands across Amazon.com and beyond. We are at the forefront of re-inventing advertising experiences, bridging human creativity with artificial intelligence to transform every aspect of the advertising lifecycle from ad creation and optimization to performance analysis and customer insights. We are a passionate group of innovators dedicated to developing responsible and intelligent AI technologies that balance the needs of advertisers, enhance the shopping experience, and strengthen the marketplace. If you\'re energized by solving complex challenges and pushing the boundaries of what\'s possible with AI, join us in shaping the future of advertising.
The Brand Stores team within Sponsored Products and Brands is chartered to create agentic brand store building experience, automating brand store creation, personalization, and optimization across global marketplaces, serving millions of brand owners world-wide.
BASIC QUALIFICATIONS
- 3+ years of building machine learning models for business application experience
- 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.
PREFERRED QUALIFICATIONS
- Experience developing, deploying and managing AI products at scale
- Experience with generative model architectures
- Research publications or patents in generative AI technologies
- Experience in Reinforcement Learning from Human Feedback (RLHF), Retrieval-Augmented Generation (RAG) and AI model trade-offs (e.g., model size, latency, cost, and output quality)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you?re applying in isn?t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at .
USA, NY, New York - 183,800.00 - 248,700.00 USD annually
USA, WA, SEATTLE - 167,100.00 - 226,100.00 USD annually
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