The Sponsored Products and Brands (SPB) team at Amazon Ads is re-imagining the advertising landscape through generative and agentic 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 to transform every aspect of the advertising lifecycle; from ad creation, delivery, optimization, performance management, and beyond. We are a passionate group of innovators dedicated to developing state-of-the-art AI technologies that balance the needs of advertisers and enhance the shopping experience. Within SPB, the SPB Offsite (SPBO) team builds solutions to extend campaigns to reach customers off the store and extend shopping experiences on third-party sites where shoppers search and discover products. We use industry-leading machine learning, high-scale low-latency systems, and gen AI technologies to create better sponsored customer experiences off the store.

The Principal Applied Scientist for SPBO leads the technical vision and scientific strategy for extending Amazon Advertising's sponsored experiences to the broader web—meeting shoppers wherever they search, browse, and discover products. This is a multi-disciplinary scientific space spanning machine learning, large-scale optimization, causal inference, NLP, information retrieval, and generative AI. You will define and drive the science roadmap for how Amazon connects advertisers with high-intent customers across third-party environments at massive scale and with low latency. As a GenAI-first organization, we build foundational and agentic models that power advertiser use cases across Ads, while empowering our Applied Scientists to directly build and ship products. You will be a hands-on technical leader who architects novel solutions end-to-end—from research through production—while mentoring a team of scientists across diverse domains.

The problems you will tackle are among the hardest in ad tech. You will develop models that leverage Amazon's first-party shopping signals to reach high-value audiences in third-party environments where signal density differs fundamentally from on-Amazon contexts. You will innovate on real-time bidding, auction dynamics, and ranking models across heterogeneous supply sources with distinct inventory characteristics, latency constraints, and auction mechanics. You will design ML approaches that maintain effectiveness amid an evolving privacy landscape—turning constraints from cookie deprecation, regulation, and platform restrictions into innovation opportunities. You will influence attribution models that capture the incremental value of offsite advertising on shopping outcomes, bridging measurement gaps between offsite touchpoints and on-Amazon conversions. You will pioneer generative and agentic AI to personalize ad creatives and shopping experiences for offsite contexts, and develop scientific frameworks to optimize spend allocation across supply partners and channels.

You will partner with engineering, product, and business leaders as well as external partners to shape product strategy with scientific insight and drive results at scale. You will represent Amazon Advertising's offsite science externally through patents and industry engagement.

• Key job responsibilities

• Driving the scientific vision of the teams in your organization and advising and influencing its technical leadership on ad serving, bidding, ranking, and offsite advertising models and products.

• Identifying, tackling, and proposing innovative solutions to intrinsically hard, previously unsolved problems in offsite ad tech.

• Bringing clarity to complex problems, probing assumptions, illuminating pitfalls, fostering shared understanding, and guiding towards effective solutions.

• Serving and being recognized by internal and external peers as a thought leader in offsite advertising science, including real-time bidding, personalization, privacy-preserving ML, and generative AI for ad experiences.

• Influencing your team's science and business strategy by driving one or more team roadmaps contributing to the organization's roadmap and taking responsibility for some organizational goals. You drive multiple new product features from inception to production launch.

• Guiding the career development of others, actively mentoring and educating the larger applied science community on trends, technologies, and best practices.

Basic Qualifications

• 5+ years of hands-on work in predictive modeling and analysis experience
• PhD in Electrical Engineering, Computer Science, Mathematics, or a related technical field
• Experience working in predictive modeling and analysis
• Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
• Experience programming in Java, C++, Python or related language
• Experience with leading experienced scientists as well as having a record of developing junior members from academia or industry to a career track in a business environment

Preferred Qualifications

• 10+ years of relevant work in industry or academia experience
• Knowledge of problem solving, algorithm design and complexity analysis
• Experience creating novel algorithms and advancing the state of the art
• Have peer-reviewed scientific contributions in premier journals and conferences

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 https://amazon.jobs/content/en/how-we-hire/accommodations 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 https://amazon.jobs/en/benefits.

USA, CA, Palo Alto - 228,700.00 - 309,400.00 USD annually
USA, NY, New York - 218,800.00 - 295,900.00 USD annually
USA, WA, Seattle - 198,900.00 - 269,000.00 USD annually