Senior Applied Scientist - Sponsored Products

Description

The Sponsored Products and Brands team at Amazon Ads is re-imagining the advertising landscape through cutting-edge 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 Sponsored Products Search Sourcing Science (SPSSS) team's mission is to retrieve all relevant sponsored products in response to shopper queries, serving billions of daily ad impressions and tens of millions of clicks, helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this, we build state-of-the-art capabilities spanning query, shopper, product, and advertiser understanding, as well as advanced retrieval, targeting, and ranking systems, all powered by efficient large-scale data pipelines, deep learning, natural language processing (NLP), generative AI, and multi-agent workflows. It's a high-impact, technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.

Key job responsibilities
As a Senior Applied Scientist on this team, you will:
- Serve as the technical leader in Machine Learning and Generative AI, driving efforts within this team and across other teams.
- Lead end-to-end ML projects with high ambiguity, scale, and complexity—from problem definition to production.
- Build, optimize, and deploy ML models into production, partnering with software engineers to productionize solutions.
- Establish scalable, automated processes for data analysis, model development, validation, and serving.
- Apply strong knowledge of LLMs (prompt engineering, fine-tuning, RAG, evaluation) to build production-grade GenAI applications.
- Analyze large-scale data sets to develop insights that increase traffic monetization and merchandise sales without compromising the shopper experience.
- Design and run A/B experiments, and perform statistical analysis to measure impact and guide decisions.
- Research and prototype innovative ML and GenAI approaches, bringing state-of-the-art techniques into production.
- Recruit, mentor, and grow Applied Scientists on the team.

About the team
Amazon is investing heavily in building a world-class advertising business. This team defines and delivers a collection of advertising products that drive discovery and sales. Our solutions generate billions in revenue and drive long-term growth for Amazon’s Retail and Marketplace businesses. We deliver billions of ad impressions, millions of clicks daily, and break fresh ground to create world-class products. We are a highly motivated, collaborative, and fun-loving team with an entrepreneurial spirit - with a broad mandate to experiment and innovate.

The Sponsored Products Search Sourcing Science (SPSSS) team's mission is to retrieve all relevant sponsored products in response to shopper queries, serving billions of daily ad impressions and tens of millions of clicks, helping shoppers discover useful and contextually relevant products while enabling advertisers to reach the right shoppers in the right context. To achieve this, we build state-of-the-art capabilities spanning query, shopper, product, and advertiser understanding, as well as advanced retrieval, targeting, and ranking systems, all powered by efficient large-scale data pipelines, deep learning, natural language processing (NLP), generative AI, and multi-agent workflows. It's a high-impact, technically exciting space where science directly translates into measurable outcomes for hundreds of millions of customers and millions of advertisers.

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 with neural deep learning methods and machine learning
- Experience in building speech recognition, machine translation and natural language processing systems (e.g., commercial speech products or government speech projects)

Preferred Qualifications

- Experience with large scale machine learning systems such as profiling and debugging and understanding of system performance and scalability
- Master's degree or above in engineering, statistics, computer science, mathematics, or a related quantitative field
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 3+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing, or experience leading engineering teams as a mentor or tech lead
- Experience creating and delivering written and oral communications for technical and non-technical audiences
- Experience in data science, business analytics, business intelligence, or similar experience in big data environments
- Thinks strategically, but stays on top of tactical execution.
- Exhibits excellent business judgment; balances business, product, and technology very well.
- Experience in computational advertising.
- Experience in Large Language Models (LLMs).

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.