We are building the next generation of personalized shopping experiences at Amazon through deep understanding of our customer's intent and our product catalog. We aim to create an experience akin to that of a talented personal shopping assistant — a partner that is knowledgeable, understands your preferences, and helps you find the right solution for your needs.
As a Sr. Mgr of Applied Science on the team, you will help lead a large multidisciplinary team. You will have a breadth of problems to work on, ranging from developing state of the art LLM-based techniques to reason about customers and products, developing deep learned transformer-based models to understand and abstract customer intent signals and representations, building large-scale real-time multi-task ranking systems, and more. You will build AI primative systems to empower teams across the company to build recommendations experiences, while also having a direct connection to millions of customers through our own customer facing features every day. Come join us in the journey!
Key job responsibilities
- Own and drive the science and engineering vision and roadmap across multiple teams, setting a cohesive technical agenda that connects research investments to production systems and measurable customer outcomes
- Lead a combined organization of applied scientists and software engineers, building a culture of scientific rigor, engineering excellence, and rapid experimentation
- Architect and deliver end-to-end ML systems at Amazon scale — from model research and training through real-time serving infrastructure — for ranking, intent understanding, and personalization across all customers and countries
- Drive engineering best practices across the org, ensuring production systems meet Amazon's bar for reliability, latency, and operational excellence
- Advance the state of the art in applied ML/AI, contributing to the broader scientific community
- Mentor and grow applied scientists and engineers at all levels, developing the next generation of technical leaders in the org
- Represent the organization in leadership forums, influencing cross-org strategy and investment decisions across both science and engineering
About the team Our mission is to delight every Amazon customer with a personalized shopping experience tailed to their intent. We achieve our mission through investments in UX, Science, and Systems with the purpose of delivering the future of shopping on Amazon. We are seeking a Principal Applied Scientist to lead the science charter across the recommendations and intent identification space.
About our organization: Our team is part of Amazon’s Personalization organization, a high-performing group that leverages Amazon’s expertise in machine learning, big data, distributed systems, and user experience design to deliver the best shopping experiences for our customers. We run global experiments and our work has revolutionized e-commerce with features such as "Keep shopping for ...", “Customers who bought this item also bought”, and “Frequently bought together”. Amazon’s internal surveys regularly recognize us as one of the best engineering organizations to work for in the company, with visible high-impact work, low operational load, respectful work-life balance, and continual opportunity to learn and grow.
Basic Qualifications
- 8+ years of science or engineering team management experience
- Master's degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Knowledge of data structures, algorithm design, statistics, and system design
- Experience building large-scale machine learning and AI solutions at Internet scale
- Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
Preferred Qualifications
- PhD in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- 10+ years of building large-scale machine learning and AI solutions at Internet scale experience
- Deep expertise in one or more of: LLMs, transformer architectures, recommendation systems, real-time ranking, or representation learning
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, WA, Seattle - 218,800.00 - 295,900.00 USD annually