From Amazon's posting. “We” and “our” refer to the employer.
Reinventing How the World Shops!
We are building the future of human-AI collaboration in commerce. We are creating an AI-native shopping partner that truly understands what customers mean, what they need, and what they haven't yet realized they want—rivaling the intuition of the best human experts, operating at a scale no human ever could.
This is a complex personalization challenge. We sit at the intersection of massive-scale language understanding, real-time decision systems, hundreds of millions of customers, and billions of products. Our mission is to collapse the distance between intent and discovery—to make the leap from "searching for products" to "being understood as a person."
As a Principal Applied Scientist, you will be the intellectual engine behind this transformation. You will define the frontier, architect the science strategy for a large, multidisciplinary organization, and drive breakthroughs that reshape how Amazon thinks about customers and products at the deepest level.
The problems you'll solve don't have textbook answers. You will pioneer next-generation LLM-based reasoning systems that build rich, evolving models of customer intent. You will design transformer architectures that abstract noisy behavioral signals into high-quality latent representations of human preference. You will invent real-time, multi-objective ranking systems that balance exploration, personalization, and serendipity at billions of decisions per day.
And you will do all of this as a force multiplier, building foundational technology that empowers teams across Amazon to deliver experiences that feel almost magical.
Your work will be felt, not just measured. Every model you build ships directly to hundreds of millions of customers. The feedback loop between your science and real human delight is immediate. This role offers a rare combination of intellectual depth, technical ambition, and tangible impact.
Come define what shopping looks like in the age of AI!
Key job responsibilities
Innovate new features and models that have huge impact on the customer experience. Help customers find the right products and content on their shopping journey.
Leverage the use of advanced machine learning to create customer shopping experience at Amazon's scale - for all Amazon customers across all countries in realtime
Be a key leader on a multidisciplinary team across science, product, design, and engineering to see through ideas from inception, prototype, to launch in the hands of all Amazon's customers
Drive the science roadmap across multiple teams, helping coordinate a cohesive science agenda across the org.
Mentoring applied scientists across the org, growing their skills and careers.
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 Science, UX, and central 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.
Basic Qualifications
PhD in Computer Science, Machine Learning, Statistics, or related field, OR Master's degree and 6+ years of applied research experience
5+ years of building machine learning models for business applications, with proven track record of shipping ML-powered products to production
Deep expertise in machine learning engineering with hands-on experience building and deploying models at scale
Strong programming skills in Python, Java, C++, or related languages with ability to write production-quality code
Experience mentoring junior scientists and engineers
Experience distilling informal customer requirements into problem definitions, dealing with ambiguity and competing objectives
Preferred Qualifications
Experience creating novel algorithms and advancing the state of the art
Experience communicating with users, other technical teams, and management to collect requirements, describe software product features, and technical designs
Publications at top-tier peer-reviewed conferences (NeurIPS, ICML, ICLR, CVPR, ICCV, KDD, RecSys) or patents demonstrating technical innovation
Track record of successful production ML deployments at scale with measurable business impact
Strategic thinking combined with strong execution capability and bias for action
Experience bridging research with practical engineering implementation
Technical leadership experience in fast-paced, ambiguous environments
Equal Opportunity
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 - 198,900.00 - 269,000.00 USD annually
About this listing
LAYIQ is an independent job-discovery service. This listing does not imply a partnership with or endorsement by the employer. Review the original posting for current details and availability.
