Are you interested in shaping the future of Advertising and B2B Sales? We are a growing science and engineering team with an exciting charter and need your passion, innovative thinking, and creativity to help take our products to new heights.

Amazon Advertising is one of Amazon's fastest growing and most profitable businesses, responsible for defining and delivering a collection of advertising products that drive discovery and sales. Our products are strategically important to our businesses driving long term growth. We deliver billions of ad impressions and millions of clicks and break fresh ground in product and technical innovations every day!

Within the Advertising Sales organization, we are building a central AI/ML team and are seeking top science talent to build new, science-backed services to drive success for our customers. Our goal is to transform the way account teams operate by creating actionable insights and recommendations they can share with their advertising accounts, and ingesting Generative AI throughout their end-to-end workflows to improve their work efficiency.

As a part of our team, you will bring deep expertise in quantitative modeling (forecasting, recommender systems, reinforcement learning, causal inferencing or generative artificial intelligence) to build and refine models that can be implemented in production. You will be a key contributor as we chart new courses with our ad sales support technologies, and you have the communication skills necessary to explain complex technical approaches to a variety of stakeholders and customers. As a core team member, you will have the excitement to take iterative approaches to tackle big, long-term problems.

Why you will love this opportunity: Amazon has invested 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 ads 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.

Impact and Career Growth: You will invent new experiences and influence customer-facing experiences; this is your opportunity to work within the fastest growing businesses across all of Amazon! Define a scientific vision for our advertising sales business, driven from our customers' needs, translating that direction into specific plans for scientists, engineers and product teams. This role combines scientific innovation, organizational ability, technical strength, product focus, and business understanding.

Key job responsibilities
- Conceptualize and lead state-of-the-art research on new Machine Learning and Generative Artificial Intelligence solutions to optimize all aspects of the Ad Sales business
- Guide the technical approach for the design and implementation of successful models and algorithms in support of expert cross-functional teams delivering on demanding projects
- Conduct deep data analysis to derive insights to the business, and identify gaps and new opportunities
- Run regular A/B experiments, gather data, and perform statistical analysis
- Work closely with software engineers to deliver end-to-end solutions into production
- Improve the scalability, efficiency and automation of large-scale data analytics, model training, deployment and serving

About the team
Sales AI is a central science and engineering organization within Amazon Advertising Sales that powers selling motions and account team workflows via state-of-the-art of AI/ML services. Sales AI is investing in a range of sales intelligence models, including the development of advertiser insights, recommendations and Generative AI-powered applications throughout account team workflows.

BASIC QUALIFICATIONS

- 3+ years of building models for business application experience
- PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- Experience programming in Java, C++, Python or related language
- Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing

PREFERRED QUALIFICATIONS

- Experience using Unix/Linux
- Experience in professional software development

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, 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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $222,200/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.